Many frugal folks are geeks at heart. Now you can indulge both sides of your personality with comic books from the Federal Reserve Bank!
The Federal Reserve Bank of New York has been publishing educational cartoon-style booklets since the 1950s. "The Story of the Federal Reserve System" is one of ten titles currently available. The comic book is intended for the general public, especially students in high school and introductory-level college economic courses.
Up to 35 copies of each comic book are available free. Additional copies are 25 cents each, with exceptions for classroom use. To order, write to the Public Information Department, Federal Reserve Bank of New York, 33 Liberty Street, New York, New York 10045. These publications can also be ordered online.
Once Upon a Dime — A fable about the island kingdom of Mazuma and the growth of its economy from barter to a sophisticated modern system, with its own central bank, to iIlustrate basic concepts of barter, money, banking, and inflation.
A Penny Saved… — Illustrates the importance of savings — how it benefits all of us — and the various types of savings instruments and institutions.
The Story of Banks — Follows three young entrepreneurs as they use progressively more sophisticated bank services over a 23-year period. Also explores the role of checking deposits and lending in money creation.
The Story of Checks and Electronic Payments — Uses the story of two basketball-playing buddies to discuss the role of checks and electronic payments in the U.S. economy — including the role of the Fed in facilitating payments. The booklet also teaches personal finance skills such as writing a check and balancing a checking account.
The Story of Consumer Credit — Explains consumer rights and responsibilities and consumer credit regulations.
The Story of Foreign Trade and Exchange — Explains the basic principles underlying foreign trade and exchange.
The Story of Inflation — Describes the causes and effects of inflation and discusses alternative anti-inflation policies.
The Story of Monetary Policy — Explains the meaning and purpose of monetary policy, how the Fed makes monetary policy, and how the tools of monetary policy work.
The Story of Money — Explains the purposes of money in a modern economy, the characteristics that items used as money have, the way the banking system creates money, and the reasons the Federal Reserve influences the money supply.
The Story of the Federal Reserve System — Describes the major functions of the Federal Reserve System, the tools of monetary policy and how they work, and the other ways in which the Fed helps the U.S. economy and financial system to function.
Too Much, Too Little — Provides a history of the U.S. monetary system and events leading to the establishment of the Federal Reserve System.
I'll hand these out as stocking stuffers to my nieces and nephews this Christmas. I'm the best uncle ever!
There are 4 reader responses to "Free Comics from the Federal Reserve".
If they're all like the one available in PDF format above, I think kids are more likely to be en/discouraged to use psychedelic drugs than learn about finance from reading them. I'd say its economic message was a bit oblique, wouldn't you?
The style of the comics are a little retro, but they are "educational".
I managed to pick up a few of these free comics on my visit to see the Gold Bullion down in the New York Fed Vault!
I only see two comic books available now.


SAN JOSE, CALIF. –– February 22, 2018 — Oski Technology, Inc., the established and trusted leader in Formal verification methodology expertise, today announced that its Formal Verification business grew in 2017 to include a deep array of verification application challenges.
The result is in an unprecedented number of design bugs and corner case bugs being identified.
Oski provided expertise on more than 17 different verification projects for processor, GPU, intellectual property (IP), network on chip (NoC), switching, networking and wireless designs. Formal applications of these designs ranged from register transfer logic (RTL) control logic and data transport to architectural formal cache coherency and sequential equivalence checking. Oski's Formal Verification expertise uncovered more than 1,000 bugs with 233 of them deemed to be significant corner case bugs that would have been impractical to detect in simulation. What's more, they could have had a dramatic impact on design operation.
Oski will offer demonstrations of the Oski Formal Sign-Off Methodology™ and Abstraction Models™ to achieve End-to-End Formal™ verification and complete coverage during in DVCon Booth #205. The DVCon Expo and Reception will be held Monday, February 26, from 5 p.m. until 7 p.m. Regular exhibit hours will be held Tuesday, February 27, and Wednesday, February 28, from 2:30 p.m. until 6 p.m. DVCon will be held at the DoubleTree Hotel in San Jose, Calif.
Oski Technology established itself as the unsurpassed trusted global leader in the domain of Formal Verification methodology and expertise. Founded in 2005, Oski serves six out of the top seven semiconductor design companies. Leaders in consumer electronics, communications, computing, image processing, data storage, research, defense, education, automotive, and medical turn to Oski for help accelerating their verification process and produce higher quality designs than simulation alone allows. Oski has assembled the world's largest dedicated team of experts that draws on hundreds of man-years of collective experience to provide Oski-certified verification sign-off. Oski reset the benchmark for formal verification with innovations such as its Formal Sign-off™ methodology, End-To-End Formal™ checkers and Oski Abstraction Models™. Oski's publications, training sessions and events, such as the Decoding Formal Club, are recognized industry-wide as valuable resources of formal applications knowledge.


text:
A New Name, A New Day
In 2012 we relocated our operation from McArthur Airport in Islip, NY to Gabreski Airport in Westhampton, NY in order to expand our operational capabilities and capacity. Since relocating we have continued to enhance our operation, becoming a FAA Certified Repair Station (CRS #AOBR190C).
Expanding Our Fleet
A prime objective of our relocation was to be able to expand our fleet of aircraft. Since moving to our new facility we have added several new aircrafts.
40 Years and Counting
This year Sunrise Jets is celebrating our 40th anniversary of being in business. We are tremendously grateful to everyone that has worked as part of our team, to those who have relied on us to manage and maintain their aircrafts, and to all those who have entrusted us with their safety. Your safety and experience are responsibilities that we do not take lightly, and it has been a pleasure to serve you. We look forward to many more years of operation.
Eastway Aviation LLC was born in 1979. For over thirty five years Eastway Aviation, and now Sunrise Jets, has maintained a perfect safety record and has built a reputation as one of New York's premier aircraft management and charter flight operators.
Located in our new home at Gabreski Airport in Westhampton, New York; Sunrise Jets operates out of our own custom built, state-of-the-art 25,000 square foot hangar. We are the ideal choice for any aircraft based out of Long Island, but also have the capability to service Aircraft Charter customers and Aircraft Management customers out of any airport of their choosing. We routinely fly out all the major airports in the New York-New Jersey-Connecticut metropolitan area.
We are the largest full-service owner/operator of on-demand charter flights in the Hamptons. Unlike brokers, we not only manage and fly our aircraft, we also maintain them ourselves, to the highest standards in the industry. At Sunrise Jets, our commitment to customer service and satisfaction is second to none.
Our company is made up of people who love what they do. We love flying, we love serving, and we love the details of our business. At Sunrise Jets, we know your standards and strive every day to exceed them.
Where We Are Going
Sunrise Jets is committed to constantly raising the bar in safety and customer satisfaction, for ourselves and for the industry. Our mission is to achieve the highest standards in every area of our operations. We are excited for where our journey will take us, and we hope that you will come along for the ride.

redpajama_set_name: RedPajamaCommonCrawl


In Version 1.10, the changes include the following. All changes pertain to the poker-like Finnish 27 game. The predetermined strategy for the play of the dealer's hand is different. The description of the best strategy for the play of the player's hand is updated. A table for the basic strategy for 2 card hands is provided. A table for the exception rules for 2 card hands is provided. Tables for 3 card hands and 4 card hands are provided. Links to said tables are provided in the rules section.


Currently I have two books in print the Second Book is available in Hard Cover, Paperback or eBook format and was released May of 2009.
It is called "Are You Destined To Lead" and should be available through your local book stores and on the web.
My First Book "Ephesians: God's battle Plan For Spiritual Warfare" is available in the same formats from iuniverse publishing.
It is also available from Amazon.com, and Barnes and Noble's websites and Book Stores or other locations in your area should be able to order it for you. You may also request ordering information via the contact tab onthis website.
I would also like to recommend the following two books that I have used in my work with both law enforcement and military families that find themselves questioning their personal relationships.
The first is "Because I'm Suitable: The Journey of a Wife on Duty." Written by: Allison P. Uribe, the wife of a San Antonio Police Officer. She and her husband have three beautiful children, two boys and a little girl. She is a graduate from Providence High School and attended Our Lady of the Lake University in San Antonio, Texas. Currently, she is a Lead Community Chaplain. She has been a student with the Emergency Services Chaplains Program. Recently, she accepted an opportunity with the San Antonio Police Department and became a San Antonio Police Auxiliary Chaplain. As the founder and Chaplain of Wives on Duty Ministries, Allison has a dream to travel as a speaker and be able to encourage, hug, and love on wives of law enforcement, firefighters, and military nationwide.
The second recommendation is "Emotional Survival For Law Enforcement" By: Kevin M. Gilmartin. Dr. Gilmartin is a behavioral scientist who specializes in issues related to law enforcement. With twenty years of police experience under his belt, he currently provides service to the law enforcement community as a consultant. In writing this book, it was his goal to aid officers and their families in maintaining and/or improving their quality of life both personally and professionally.


text:
\section{Introduction}
Task-oriented dialog (TOD) systems interact with users in natural languages through multiple turns to accomplish tasks.
The system needs to parse user utterances, track dialog states, query a task-related database (DB), decide actions and generate responses, and to do these iteratively across turns.
The methodology for building TOD systems is gradually advancing from separate training of individual modules \cite{mrkvsic2017neural, dai2018tracking} to the end-to-end (E2E) trainable approach \cite{wen2017a, liu2017end, lei2018sequicity, fsdm, zhang2020task,gao2020paraphrase,zhang-etal-2020-probabilistic}.
In early E2E methods, the sequential turns of a dialog is modeled as a Markov process.
According to the conditional transitions between turns, the model reads the last dialog state, last system response and current user utterance, and generates the current dialog state and system response.
Different encoder-decoder architectures are developed to model the conditional transitions.
For example, while SEQUICITY \cite{lei2018sequicity} uses two decoders to generate belief spans and responses respectively, DAMD \cite{zhang2020task} further introduces a third decoder to explicitly generate system acts.
LABES \cite{zhang-etal-2020-probabilistic} extends SEQUICITY, as it introduces an additional encoder for dialog states and explicitly models the probabilistic transitions between dialog states across turns, and thus enables semi-supervised learning feasible.
Despite these differences, all these early E2E methods are LSTM-based, mostly augmented with copy mechanism.

Recently, self-attention based Transformer neural networks \cite{vaswani2017attention} have shown their superiority in capturing long-term dependencies over LSTM based networks. Transformer based pretrained language models (PLM), such as GPT2 \cite{radford2019gpt2} and T5 \cite{JMLR:v21:20-074}, have been leveraged to build generative E2E TOD systems in the pretraining-and-finetuning paradigm, which have shown improved performance over LSTM-based ones. Examples include GPT2-based SimpleTOD \cite{hosseini2020simple}, SOLOIST \cite{peng2020etal}, AuGPT \cite{kulhanek2021augpt} and UBAR \cite{yang2021ubar}, and T5-based PPTOD \cite{su2021multitask} and MTTOD \cite{lee-2021-improving-end}, among others.
A drawback of existing PLM-based methods is that the whole history is used as the conditioning input at each turn. The dialog model thus becomes non-Markovian across turns, i.e., the generation at current turn depends not only on the previous turn but also on all previous turns, namely the whole dialog history. While some models relies on all previous user utterances and system responses at each turn, others like UBAR and MTTOD make the generation at current turn additionally conditional on all previous dialog states, DB results, system acts.
In both manners, this non-Markovian modeling significantly increases the memory and computation cost in both training and generation.
Moreover, using the whole history may burden the model with redundant information and hurts the training efficiency.

To address the aforementioned drawback of existing PLM-based TOD systems, we propose to revisit \underline{M}arkovian \underline{G}enerative \underline{A}rchitectures (MGA) in building PLM-based TOD systems, which could be based on GPT2 or T5 but using shortened history.
The motivation is that, by definition, the dialog state refers to the state of the conversation, summarizing the dialog history from the beginning up to current turn. Thus, a shortened history, which consists of only last dialog state and system response along with current user utterance, should provide enough context information for the model to make prediction at current turn.
Such Markovian models have been successfully used in previous LSTM-based TOD systems \cite{wen2017a}-\cite{zhang-etal-2020-probabilistic} as reviewed above, but not studied for PLM-based TOD systems.
Our experiments are taken on the widely used MultiWOZ2.1 dataset \cite{eric2019multiwoz} and show that compared with existing non-Markovian PLM-based systems, the proposed Markovian PLM-based systems achieve equally strong performance, with significantly reduced computation and memory costs.
Furthermore, the superiority of the proposed Markovian models over non-Markovian ones is more evident in low-resource setting and variational semi-supervised learning \cite{liu2021variational} on the MultiWOZ2.1 \cite{eric2019multiwoz} dataset.
Overall, to our knowledge, these results represent the first strong empirical evidence supporting the advantage of using Markovian architectures for PLM-based TOD systems.

\section{Method}
\label{sec:method}
In TOD systems, let $u_t$ denote the user utterance, $b_t$ the dialog state, $db_t$ the DB result, $a_t$ the system act and $r_t$ the delexicalized response, respectively, at turn $t=1,\cdots,T$, for a dialog of $T$ turns. In this work, all these variables are converted to token sequences, following recent studies in \cite{zhang2020task,zhang-etal-2020-probabilistic}.

The work flow for a TOD system is, for each dialog turn $t$, to generate (or say, predict) $b_t$, $a_t$ and $r_t$ \footnote{Note that database result $db_t$ is deterministically obtained by querying database using the predicted $b_t$. We omit $db_t$ in the discussion for simplicity.}, given $u_t$ and dialog history $u_1, r_1, \cdots, u_{t-1}, r_{t-1}$.
In recent PLM-based TOD systems, such work flow of a dialog system is unified into a single sequence generation problem, which can be accomplished by finetuning PLMs, such as GPT2 \cite{radford2019gpt2} and T5 \cite{JMLR:v21:20-074}\footnote{In this paper, when referring to PLMs, GPT2 and T5 are used as typical examples. GPT 2 is a decoder-only PLM and T5 is an encoder-decoder PLM. Both are based on self-attention based Transformer neural networks \cite{vaswani2017attention}.}.
The basic idea is that for building a particular conditional model, $p(output|input)$, where $input$ and $output$ are token sequences, a PLM can be finetuned over training samples $(input, output)$ (often referred to as training sequences \cite{hosseini2020simple}), and after finetuning, the model can be used for generation, i.e., generating $output$ after receiving $input$.
Different PLM-based dialog models employ different architectures for $p(output|input)$.
For example, the generative architecture used in SimpleTOD \cite{hosseini2020simple} is described by
\begin{equation} \label{eq:SimpleTOD}
p(b_t, a_t, r_t|u_1, r_1, \cdots, u_{t-1}, r_{t-1}, u_t),
\end{equation}
as shown in Fig. \ref{fig:SimpleTOD} and the one used in UBAR \cite{yang2021ubar} is
\begin{equation} \label{eq:UBAR}
p(b_t, a_t, r_t|u_1, b_1, a_1, r_1, \cdots, u_{t-1}, b_{t-1}, a_{t-1}, r_{t-1}, u_t),
\end{equation}
as shown in Fig. \ref{fig:UBAR}.

A drawback of existing PLM-based systems is that they assume non-Markovian transitions across turns, as can be seen from the transition distributions in Eq. \eqref{eq:SimpleTOD} and \eqref{eq:UBAR}.
This brings inefficiencies in memory, computation and learning.
To address this drawback, we revisit Markovian generative architecture (MGA), which, with parameter $\theta$, is designed to be
\begin{equation} \label{eq:MGA}
p_{\theta}(b_t, a_t, r_t|b_{t-1}, r_{t-1}, u_t),
\end{equation}
as shown in Fig. \ref{fig:MGA}.
Specifically, to predict $b_t$, $a_t$ and $r_t$ at each turn $t$, we propose to use only the belief state $b_{t-1}$ and response $r_{t-1}$ from previous turn along with current user utterance $u_t$, instead of using the whole dialog history, as the conditioning input.
Presumably, using such shortened history is reasonable since, by definition, belief state $b_{t-1}$ is generally a summary of dialog history up to turn $t-1$, which, together with $r_{t-1}$ and $u_{t}$ , should carry enough context information for the model to make prediction for $b_t$, $a_t$ and $r_t$.

Empirically, it is found that earlier history turns beyond the previous turn are in fact weakly attended to in next-token generation (see Sec. \ref{sec:analysis}). It is also shown later in Fig. \ref{fig:memory} and Table \ref{tab:speed} that with MGA, the memory cost in training, the training and inference time can be significantly reduced, while achieving state-of-the-art result on MultiWOZ2.1.
It is also reported in \cite{JEON2022101310} that the use of the whole dialogue history increases the training cost.

In supervised learning, the generative model in Eq. \eqref{eq:MGA} can be finetuned from PLMs such as GPT2 or T5, by maximizing the following conditional likelihood:
\begin{equation}
\label{eq:sup-ds}
\begin{aligned}
    \mathcal{J}_{\text{MGA}} &=\log p_{\theta}(b_t, a_t, r_t|b_{t-1}, r_{t-1}, u_t)\\
    &= \sum_{i=1}^{|b_t \oplus a_t \oplus r_t|} \log p_\theta(c_i| b_{t-1}, r_{t-1}, u_t, c_{<i})
\end{aligned}
\end{equation}
where $\oplus$ denotes the concatenation of sequences, $|b_t \oplus a_t \oplus r_t|$ denotes the length of $b_t \oplus a_t \oplus r_t$ in tokens and $c_i$ denotes the $i$-th token in  $b_t \oplus a_t \oplus r_t$.

For running variational semi-supervised learning with the generative model in Eq. \eqref{eq:MGA}, an inference model also with Markovian architecture can be similarly designed as follows:
\begin{equation} \label{eq:MGA-inf}
q_{\phi}(b_t, a_t|b_{t-1}, r_{t-1}, u_t,r_t),
\end{equation}
as shown in Fig. \ref{fig:MGA-inf}.
The supervised training of Eq. \eqref{eq:MGA-inf} and the variational learning of Eq. \eqref{eq:MGA} and \eqref{eq:MGA-inf} are omitted to save space, which are similar to the non-Markovian settings in \cite{liu2021variational}.

\begin{figure}[t]
	\centering
	\subfigure[Architecture of SimpleTOD]
	{\label{fig:SimpleTOD}
	\includegraphics[width=\columnwidth]{figs/SimpleTOD.png} }
	\subfigure[Architecture of UBAR]
	{\label{fig:UBAR}
	\includegraphics[width=\columnwidth]{figs/UBAR.png} }
	\subfigure[Architecture of MGA generative model]
	{\label{fig:MGA}
	\includegraphics[width=\columnwidth]{figs/MGA.png}}
	\subfigure[Architecture of MGA inference model]
	{\label{fig:MGA-inf}
	\includegraphics[width=\columnwidth]{figs/inference.png} }
	\caption{Different architectures for $p(output|input)$ in different PLM-based TOD systems.
	Yellow boxes represent the conditioning $input$ of the model during generation, and green boxes the targeting $output$.
}
	\label{fig:structure}
	\vspace{-0.5em}
\end{figure}

\vspace{-1em}
\section{Experiments}
\label{sec:exp}
\subsection{Datasets}
Experiments are conducted on MultiWOZ2.1 \cite{eric2019multiwoz}. MultiWOZ2.1 is an English multi-domain TOD dataset, collected via human-to-human interactions using the Wizard-of-Oz approach. It consists of a total of 10.4k dialog sessions, spanning over seven domains (restaurant, train, attraction, hotel, taxi, hospital, police).
Compared to MultiWOZ2.0, MultiWOZ2.1 removed some noisy state values.
We further removed some inappropriate state values and corrected some spelling errors in the dataset\footnote{All the code and data will be released upon the acceptance of the paper.}.

\vspace{-0.5em}
\subsection{Evaluation metrics}
Different dialog systems are evaluated in the end-to-end setting, which means that the generated dialog states and system acts are used in response generation.
To avoid any inconsistencies in evaluation and rigorously compare our models with others, we use the standardized evaluation scripts in \cite{nekvinda-dusek-2021-shades}, which are now also the scripts adopted in the MultiWOZ website.
There are mainly four metrics for corpus-based evaluation. \emph{Inform Rate} measures how often the entities provided by the system are correct. \emph{Success Rate} refers to how often the system is able to answer all the requested attributes by user. \emph{BLEU Score} is used to measure the fluency of the generated responses. And the \emph{Combined Score} is computed as (BLEU + 0.5 * (Inform + Success)).

\begin{table}[t]
\caption{Results on MultiWOZ2.1. Above the dashed line are cited from the official website of MultiWOZ (marked with ${\dagger}$), and below are statistical results obtained by our own run with 3 different random seeds.}
\centering
\resizebox{\linewidth}{!}{
\begin{tabular}{lccccc}
\hline
\textbf{Model} &PLM &Inform &Success &BLEU &Combined\\
\hline
UBAR$^{\dagger}$ &GPT2 &83.4	&70.3 &17.6	&94.4\\
MTTOD$^{\dagger}$ &T5 &85.4 &75.7 &19.64 &100.2\\
\hdashline
SimpleTOD &GPT2 &82.23$\pm$1.09 &69.13$\pm$0.65 &18.23$\pm$0.26 &93.92$\pm$1.11\\
UBAR &GPT2 &84.60$\pm$1.00 &73.13$\pm$1.03 &18.54$\pm$0.11 &97.40$\pm$1.03\\
MGA-GPT2 &GPT2 &84.50$\pm$0.29  &72.77$\pm$0.50  &18.96$\pm$0.36  &97.59$\pm$0.54\\
MTTOD &T5 &85.67$\pm$0.61 &75.97$\pm$0.45 &19.62$\pm$0.23 &100.43$\pm$0.67\\
MGA-T5 &T5 &84.63$\pm$0.82  &75.17$\pm$1.11  &19.49$\pm$0.15  &99.39$\pm$0.63\\
\hline
\end{tabular}
}
\label{tab:baseline}
\vspace{-1em}
\end{table}

\vspace{-0.5em}
\subsection{Benchmarking results}
The results for different models trained with 100\% labeled data are shown in Table~\ref{tab:baseline}.
The results in the upper block are given for reference and not directly comparable to the lower block in Table~\ref{tab:baseline}, due to our cleanup of the dataset. The results in the lower block can be strictly compared to each other.
The MGA models trained with the backbones of GPT2 and T5 are denoted by MGA-GPT2 and MGA-T5 respectively.
In terms of mean Combined Score, MGA-GPT2 achieves the best performance among all the GPT2 based models and MGA-T5 performs slightly worse than MTTOD. More rigorously, we conduct significance tests between the proposed MGA models and the state-of-the-art (SOTA) models with different backbones of GPT2 and T5, respectively. The McNemar test is used for \emph{Inform} and \emph{Success} and the matched pair test for \emph{BLEU} \cite{gillick1989some}. The p-values are reported in Table~\ref{tab:p-value}. All the p-values are pretty large, indicating that the differences between the models being compared are not significant and the proposed Markovian models performs as strongly as the SOTA non-Markovian models - UBAR and MTTOD.

Furthermore, it can be seen from Fig.~\ref{fig:memory} that MGA-GPT2 consumes much less memory (reduced by 76\%) than SimpleTOD and UBAR during training, as the training sequences for the Markovian model are generally much shorter than the non-Markovian models.
For time cost, we run the GPT2-based models on a single GPU (Tesla P100), record the total training time and the inference time on test set and report them in Table~\ref{tab:speed}. The same training strategy is used to train all models, where the maximum epoch is 50 and early stopping is applied. It is clear from Table \ref{tab:speed} that MGA-GPT2 reduces training time and inference time by at least 45\% and 17\% respectively, compared to the two GPT2-based non-Markovian models.

\begin{table}[t]
\caption{P-values for different metrics between different models.}
\centering
\resizebox{0.8\linewidth}{!}{
\begin{tabular}{lccc}
\toprule
Model &Inform &Success &BLEU\\
\midrule
MGA-GPT2 vs UBAR &0.116 &0.863 &0.067\\
MGA-T5 vs MTTOD &0.110 &0.290 &0.494\\
\bottomrule
\end{tabular}
}
\label{tab:p-value}
\end{table}

\begin{table}[t]
\caption{Time costs of different models in training and testing.}
\centering
\resizebox{0.7\linewidth}{!}{
\begin{tabular}{lcc}
\toprule
Model & Training Time & Generation Time Over Test Set\\
\midrule
SimpleTOD &396 min &276 s\\
UBAR &369 min &352 s\\
MGA-GPT2 &204 min &229 s\\
\bottomrule
\end{tabular}
}
\label{tab:speed}
\vspace{-1em}
\end{table}

\begin{figure}[t]
\includegraphics[width=0.85\linewidth]{figs/memory.png}
\caption{The memory costs during training with batch size 4, as a function of the lengths of training sequences.
For MGA-GPT2, SimpleTOD and UBAR, the means and standard deviations of the lengths of training sequences are 98$\pm$30, 190$\pm$112 and 440$\pm$220, respectively. The maximum sequence lengths for the three models are marked in the figure.}
\label{fig:memory}
\end{figure}

\begin{table}[t]

    \caption{Results for low-resource and semi-supervised learning of different GPT2 based models.}
	\centering
	\resizebox{\linewidth}{!}{
			\begin{tabular}{cl cccc}
				\toprule
				\multicolumn{2}{c}{Model Configuration} &\multicolumn{4}{c}{MultiWOZ2.1}\\
				\cmidrule(lr){1-2} \cmidrule(lr){3-6}
				Label Proportion &Method  &Inform &Success &BLEU &Combined\\
				\midrule

				\multirow{4}{*}{20\%} &Supervised Non-Markov  &65.30 & 50.70 & 16.79 & 74.79\\%&58.21  &64.53  &31.32  &92.69\\
				&Supervised Markov  &75.25  &59.90  &16.73  &{84.31} \\%&64.33 & 76.32 & 30.78 & 101.11 \\
				&Semi-Supervised Non-Markov &72.40 & 60.30 & 18.00 & 84.35\\%&60.68  &76.31  &37.43  &105.92\\
				&Semi-Supervised Markov  & 80.90  & 67.40  & 18.53  &{92.68}\\
				\midrule

				\multirow{4}{*}{10\%} &Supervised Non-Markov   &48.20 & 35.70 & 15.00 & 56.95 \\%&54.92  &60.60  &29.12  &86.88\\
				&Supervised Markov  &67.75  &49.60  &15.36  &{74.03}\\%&62.90 & 73.94 & 29.35 & 97.77 \\
				&Semi-Supervised Non-Markov   &69.60 & 58.30 & 16.69 & 80.64\\
				&Semi-Supervised Markov   &79.75  &66.10   & 16.78  &{89.89}\\%&64.18 & 83.02 & 36.74 & {110.34}\\
				\midrule

		\end{tabular}}
		\label{tab:semi-results}
		\vspace{-1em}
\end{table}

\vspace{-0.5em}
\subsection{Results in low-resource and semi-supervised learning}
To further evaluate the Markovian and Non-Markovian models in learning-efficiency, we randomly draw some proportions of labeled training data (10\% and 20\% with the rest being unlabelled) and conduct two types of experiments (low-resource and semi-supervised) over MultiWOZ2.1.
The results are shown in Table \ref{tab:semi-results}, where the Markov model is MGA-GPT2, the non-Markov model is the generative model in \cite{liu2021variational}, and both use GPT2 as the backbone.
In low-resources experiments, only the small amounts of labeled data are used to train the models by supervised learning, which are then used for testing.
In semi-supervised experiments, after trained with the small amounts of labeled data, the models are further trained using both labeled and unlabeled data by variational learning, as described in \cite{liu2021variational}.
It can be seen from Table \ref{tab:semi-results} that the Markov model outperforms the non-Markov model by large margins consistently across all conditions
with different labeling proportions and in both low-resource and semi-supervised settings).
These results clearly show the advantage of the Markov model over the non-Markov models in learning-efficiency, and the gains are more significant in these limited training data scenarios.

\subsection{Analysis and case study}
\label{sec:analysis}

\begin{figure}[t]
	\centering
	\begin{minipage}[t]{0.49\linewidth}
	\subfigure[UBAR]
	{\label{fig:attention_ubar}
	\includegraphics[width=\linewidth]{figs/attention_b_ubar.png}}
    \end{minipage}
    \begin{minipage}[t]{0.49\linewidth}
	\subfigure[MGA-GPT-2]
	{\label{fig:attention_mga}
	\includegraphics[width=\linewidth]{figs/attention_b.png} }
    \end{minipage}
	\caption{Average attention weights of UBAR and MGA-GPT2 for predicting the dialog state in the 4-th turn.}
	\label{fig:attention}
	\vspace{-0.5em}
\end{figure}

Inspired by the definition of dialog states and the past success of LSTM-based Markovian TOD systems \cite{lei2018sequicity,zhang2020task,zhang-etal-2020-probabilistic}, we propose that $b_{t-1}$, $r_{t-1}$ and $u_t$ could be sufficient for PLM-based dialog systems to generate $b_t$, $a_t$ and $r_t$, and the whole dialog history contains redundancy. To support this idea, we calculate the average attention weights, which represent how much the model attends to previous turns when they make predictions in a certain turn $t$.
We compare MGA-GPT2 with UBAR \cite{yang2021ubar}. Let $t=4$ and Fig.~\ref{fig:attention} shows the average attention weights over test set during generating $b_4$.
From Fig.~\ref{fig:attention_ubar}, we can see that in UBAR, dialog state $b_4$ mainly attends to current user utterance ($u_4$) and dialog states of all previous turns ($b_1$, $b_2$ and $b_3$).
Note that dialog state is defined as the accumulation of history information, which means that $b_3$ contains almost all the slots and values of $b_1$ and $b_2$. Thus, the attentions to $b_1$ and $b_2$ are redundant, they appear mainly because there are no mechanism to reduce such redundant attention in previous models.
In Fig.~\ref{fig:heat}, we provide an example to show how UBAR attends to previous dialog states and it can be seen that the tokens in $b_1$ and $b_2$ with major attention are all appeared in $b_3$.
\begin{figure}[ht]
	\includegraphics[width=\linewidth]{figs/heatmap_b.png}
	\caption{The heat map of attentions. The vertical axis represents the dialog state at the $4$-th turn, the horizontal axis represents the dialog states of history turns ($b_{1:3}$ are merged together). }
	\label{fig:heat}
\vspace{-0.5em}
\end{figure}
This suggests that, if we do not let the model attend to $b_1$ and $b_2$, the model will naturally attend more to $b_3$ and still not miss the information in $b_1$ and $b_2$.
This can be indeed observed from the attention weights of the proposed MGA-GPT2, as shown in Fig.~\ref{fig:attention_mga}. We can see that MGA-GPT2 attends much more to $b_3$ when generating $b_4$, while in UBAR, these attentions are scattered across $b_1,b_2,b_3$.
\begin{table}[t!]
\caption{A dialog example when only fine-tuned on 20\% of MultiWOZ2.1 training data. Tokens with square brackets are placeholders after delexicalization.}
\centering
\renewcommand{\arraystretch}{1.1}
\resizebox{\linewidth}{!}{
\begin{tabular}{ll}
\toprule[1.2pt]
\multicolumn{2}{c}{\textbf{MUL0739}}\\
\hline\hline
$u_1$ &Hi I need to find a place to stay with a 3 star rating with free parking.\\
$b_1$ &[hotel] parking yes stars 3\\
\multirow{2}{*}{$r_1$} &There are [choice] [stars] star [type] in cambridge. Do you have a preferred\\
&price range?\\
\hdashline
$b_1$-N.M. &[hotel] parking yes stars 3\\
\multirow{2}{*}{$r_1$-N.M.} &There are [choice] places that meet your criteria. Do you have a preferred\\
&location in the city so we can narrow down your choices?\\
\hdashline
$b_1$-MGA &[hotel] parking yes stars 3\\
\multirow{2}{*}{$r_1$-MGA} &There are [choice] places that meet your needs. Do you have a certain\\
&area or price range you are looking for?\\
\hline
$u_2$ &Could you find me one that is cheap?\\
$b_2$ &[hotel] parking yes stars 3 pricerange cheap\\
$r_2$ &There is none that is [price]. Would you like to change your criteria?\\
\hdashline
$b_2$-N.M. &[hotel] parking yes stars 3 pricerange cheap\\
$r_2$-N.M. &I am sorry, but there are no [stars] star [type] in [area] with free parking.\\
\hdashline
$b_2$-MGA &[hotel] parking yes stars 3 pricerange cheap\\
\multirow{2}{*}{$r_2$-MGA} &I am sorry, there are no [price] places in the [area]. Would you like to try\\
&a different area?\\
\hline
$u_3$ &What about cheap 4 star hotels?\\
$b_3$ &[hotel] parking yes stars 4 pricerange cheap\\
\multirow{2}{*}{$r_3$} &I have [choice] [type] and [name] that meet your needs. Would you like to\\
&book one?\\
\hdashline
$b_3$-N.M. &[hotel] parking yes  \textcolor{red}{stars 3} pricerange cheap\\
\multirow{2}{*}{$r_3$-N.M.} &I am sorry, but there are no [stars] star [type] in the [area] with free parking.\\
&Would you like to try a different area?\\
\hdashline
$b_3$-MGA &[hotel] parking yes  \textcolor{blue}{stars 4} pricerange cheap\\
$r_3$-MGA &[name] is available. Would you like me to book you a room?\\
\bottomrule[1.2pt]
\end{tabular}
}
\label{tab:case}
\vspace{-1em}
\end{table}

We provide a testing example in Table~\ref{tab:case}.
It can be seen that the Non-Markov (N.M.) model predicts a wrong star value (marked in red), which further leads to an inappropriate response. The proposed MGA successfully tracks the change of dialog state (in blue) and generates an appropriate response.
Using the whole history at each turn is redundant and even maybe harmful for learning efficiency, particularly when, as shown in this example, there are goal changes from the users.

\begin{comment}
\begin{table}[t]
\caption{A dialog state tracking case where the user changes his goal frequently during interaction. BS-UBAR and BS-MGA denotes the sequence form of dialog states generated by UBAR and MGA-GPT respectively.}
\centering
\resizebox{\linewidth}{!}{
\begin{tabular}{ll}
\toprule[1.2pt]
User &I want to find a moderate hotel in the south.\\
BS-UBAR &[hotel] area south pricerange moderate\\
BS-MGA &[hotel] area south pricerange moderate\\
\hline
User &I change my mind, I want to find a cheap one.\\
BS-UBAR &[hotel] area south pricerange cheap\\
BS-MGA &[hotel] area south pricerange cheap\\
\hline
User &Ummm, maybe moderate one is better.\\
BS-UBAR &[hotel] area south pricerange moderate\\
BS-MGA &[hotel] area south pricerange moderate\\
\hline
User &Forget it, I'd better have it cheap.\\
BS-UBAR &[hotel] area south pricerange \textcolor{red}{moderate}\\
BS-MGA &[hotel] area south pricerange \textcolor{blue}{cheap}\\
\bottomrule[1.2pt]
\end{tabular}
}
\label{tab:case}
\end{table}
\end{comment}

\section{Conclusion}
A drawback of existing PLM-based models is their non-Markovian architectures across turns, which brings inefficiencies in memory, computation and learning.
Motivated by the definition of dialog states and the past success of LSTM-based Markovian TOD systems, we propose to revisit and design Markovian Generative Architectures (MGA) for efficient PLM-based TOD systems, which could, but not limited to, be based on GPT2 and T5.
Benchmark experiments on MultiWOZ2.1 show the efficiency advantages of the MGA models, compared to their non-Markovian counterparts.
For example, MGA-GPT2 performs as strongly as the GPT2-based non-Markovian models (SimpleTOD and UBAR), while reducing training memory cost, training time, and inference time by over 76\%, 45\% and 17\% respectively.
The learning-efficiency of the MGA models is more evident in low-resource and semi-supervised learning setting.
We hope the finding in this work would be helpful for future work to develop efficient TOD systems.

\begin{comment}
\end{comment}

\bibliographystyle{IEEEtran}

redpajama_set_name: RedPajamaArXiv


Ok, if you have not trotted over to Robot6 to see what Chuck Austen has to say about his experiences with Tokyopop and everything he has encountered in his career, stop reading this, and trot on over there. You can read the rest of my opinion later on.
Oh good you are back, so here is the deal, I am an Anime/Manga fan from many moons back. So I have been unhappy with how the Anime/Manga markets are going as evidenced by the near impossibility of finding cool Anime stuff to sell, let alone selling it for any price once it hits the market place. But here comes Chuck telling us that he is making money off the industry, which warms my dark flabby heart. Because while I worry about an industry that has contracted 66% over six years, it is good to hear anyone that has survived and thrived post Tokyopop melting down.
This makes me happy. Because he is dead right.
And that is one of the things I think we consistently miss as we look at the market place. We all learn really cool things along the way. We learn what it is like to crank out a novel, a Manga book, a comic book, or heck even manage and maintain a web site like this. We have the things we learned, and we can apply those to new situations, new places, and in many cases make a couple of coins of it. I have also self-published a couple of technical books, no marketing, and they make about 100 dollars a month. They are not best sellers, but people hunt them down and at 4.99 they seem to do ok. I am sure they would do much better at 99 cents, but there is some pride in there as well, so 4.99 helps cover the costs of developing the darn thing.
You really should listen to what he has to say, it is beautiful, and wonderful, and so full of hope for the future of the industry that you can't help but pause and stop for a minute. North America and its market is not the only place in the world. You might want to localize it, but you know my books do better in India than they do in America. That is something to think about, and something you might want to check out as an independent artist. It looks like it will be totally worth your time.


Marussia Beverages UK are importers and distributors of the finest spirits from around the world. Since 1984 we have been sourcing rare and wonderful premium spirits to share with our customers. We import and distribute a very wide range of spirits including Bourbon, Scotch, Irish and World Whiskies, unique American and London dry Gin, superb French and Italian liqueurs, premium rum from Barbados and the highest quality traditional brandy from Cognac and Armagnac.
Our brands have always been about the provenance allied to the highest quality. Marussia Beverages do not just import and represent brands but we also have our own including Mamont Vodka from Siberia and the independently bottled Mezan Rum range from the Caribbean. The brands that trust us to represent them in the UK cover all the categories with a strong gin presence both from our London and UK home (Fifty Pounds Gin, NEW Barber's Gin, NEW Porter's Gin) and abroad (Aviation, Death's Door, Zuidam) as well as Briottet liqueurs from France and Tosolini from Italy. And our whiskies live up the billing too with Heaven Hill's comprehensive range from USA, Teeling from Ireland, Mackmyra from Sweden, Millstone from Holland as well as Scotch from the pioneers at Compass Box.
How would you describe the culture at Marussia?
Marussia Beverages is about empowerment. Our Business Development Managers are encouraged to think like entrepreneurs and run their regions as microcosms of the larger business with profit and loss responsibility, supporting events and results .
It is also a place with many future opportunities having recently acquired Akashi Sake Brewery in Japan and built Torabhaig on the Isle of Skye. There have been some amazing photographs and there will soon be considerable Press Coverage of the former cattle steading that is now a truly beautiful distillery on the Isle of Skye. Meanwhile we Akashi Sake Brewery have featured in many beautiful presentation pertaining to the Cunard Liners with whom we work and to whom we are very proud to supply sake.
We have a lot of in house training on Product Knowledge which is an area in which we excel. There is also an annual training budget and employees are encouraged to highlight courses that may be to our mutual benefit.
What's the best thing about working for Marussia Beverages?
We have a great reputation in the trade – and whenever we pick up the phone our clients are pleased to hear from us and talk to us.


Last month, I did a review of the cookbook, The Vegetable Butcher. Today I'm sharing a quinoa and asparagus recipe inspired by one of the recipes in the book. Lemon Vinaigrette Quinoa with Asparagus, Hazelnuts, and Mint makes a wonderful healthy side dish or vegetarian main dish that is sure to please your family and friends!
Ever since my son became a vegetarian, we've eaten a lot more interesting grains in this house. I'm no stranger to quinoa and I hope you aren't either. It's one of the few grains that is also a complete protein, which translates to "really good for you!" It's very easy to cook (just like rice!) and it has a nutty taste and a chewy bite to it. We really like it.
Like rice, it is kind of bland on it's own. That's why I like to serve it in dishes like this one, which is full of flavor! Asparagus is a great addition to the dish, adding flavor and texture. The hazelnuts give it more flavor and a nice crunch! If you don't have hazelnuts, substitute walnuts instead. The lemon vinaigrette makes a tasty dressing for the dish.
This dish can be served warm or at room temperature making it a great choice for pot lucks! You don't have to be a vegan or vegetarian to enjoy it either. It goes great with grilled chicken for an easy summer meal!
This quinoa and asparagus recipe finds it's way on my menu often and I feel really good about serving it to my family. It's wholesome and delicious and even my picky husband loves it! I hope you give it a try.
A lovely spring/summer quinoa side dish or vegetarian main dish with the flavors of lemon and mint.
Heat medium skillet on med heat. Spray with cooking spray or add 1 tsp. olive oil. Saute asparagus until crisp tender, about 5-6 minutes. Remove from heat and set aside.
Make Lemon Vinaigrette: Combine all ingredients with whisk in large bowl except olive oil. While whisking, drizzle in olive oil and whisk until it comes together.
Add quinoa, cooked asparagus, hazelnuts and mint leaves to the vinaigrette and stir to coat. Taste for salt and pepper and adjust as needed. Serve warm or at room temperature as a side dish or vegetarian main dish.
Interested in more recipes from The Vegetable Butcher? Check out this Parsnip-Ginger Layer Cake!
Both of my kids have 'attempted' to become vegetarian, but failed. But they and I, continue to include more meatless recipes in our nutrition. I'm a freak about rice and quinoa too, so this would be a winner in my family! Thanks for sharing this, Renee!
He's been going strong for about a year now. I admire him. I couldn't do it. lol I think you'll love this recipe!
Oh My! I have always wanted to try lemon and quinoa. This looks so very delicious.
Give this one a try! I think you'll like it! Thanks Rini!


This semester long course will examine the democratic foundations, structures, and institutions of American government at local, state, and national levels. Students will study the political processes to gain understanding of the role of the individuals in the decision-making process of American government. Students will also learn about the rights and responsibilities of the citizens of the United States. By investigate American government though a variety of methods, including examining primary source documents, conducting research projects, class discussion, and written essays students will gain a deeper understanding of the function of the United States Government.
- Forum 4.3 - Most Pressing Issue?
- Forum 4.4 - Biggest Threat to World Peace?
+ TEDEd - How is Power Divided?
- Socratic Discussion - The American "Nation"


Fashion designer Grandy C. is seeing red for her latest collaboration.
The Edgemont Village area resident was chosen to create a vibrant piece which was premiered Tuesday by Miss Chinese Vancouver at the kickoff for the upcoming LunarFest celebrations in Vancouver.
For her couture design, Grandy drew inspiration from the fusion-style paintings, specifically cockscomb still life, created by Italian missionary and 18th-century Chinese court painter Giuseppe Castiglioni.
The dress holds the classic silhouette of a feminine gown, with texture and embellishments to mirror the unique fur-like blossoms found on the cockscomb flower.
"When I first saw Castiglioni's still life of the cockscomb, the dress came to me right away," explains Grandy, who last year viewed some Castiglioni's work housed at the National Palace Museum of Taiwan.
The cockscomb is considered an auspicious flower in Chinese culture due to its resemblance to the chicken – an animal prized for its punctuality and work ethic, says Grandy. This flower is often gifted to celebrate career accomplishments.
Because it is a couture gown, the majority of the dress is actually hand sewn. Some 250 dyed feathers are attached to the crepe-based bodice by hand. The skirt is made from eight layers of hand-pleated organza in red and burgundy, finished with more than 70 feet of fur-trim attached also by hand.
All in it took Grandy and her team more than 100 hours to complete the dress.
The pairing of a second couture piece designed by Grandy – an inner dress shirt with a hand-embroidered, gem-studded Mandarin collar – evokes traditional Chinese dress elements, while its green tones call to the lush, tubular stems of the plant.
The dress will be on display at Oakridge Centre until Feb. 19 inside a box that Grandy designed based on the pop art interpretation of the chinoiserie style, which lends to the narrative of east-west exchange.
A chinoiserie, or a "thing of chinoise," first became a European decor style in the 17th century, after traders discovered the art of the Orient.
For this Oakridge LunarFest exhibit, Grandy is excited to partner with the National Palace Museum of Taiwan.
LunarFest, a legacy event of the Vancouver Winter Olympics, showcases contemporary expression in Asian arts and culture, while fostering collaborations between Canadian and international artists and institutions.
The Year of the Pig will be feted with several cultural events around Vancouver for the next two weeks, including the presentation of An Accident of Love musical at The Centre, and a Coastal Lunar Lantern installation at Jack Poole Plaza.
Trained as a classical pianist and graduating from Simon Fraser University with a business degree, Grandy pursued a career in the finance industry.
Her experiences in a regimented office environment led her to explore alternative career paths, so she turned to one of her longtime passions of dressmaking.
In 2013, Grandy started making one dress a week, and launched ADressAWeek.com to blog about her journey.
Her early exposure to art and music history leads Grandy to draw much of her creative inspiration from the stories and history of great art.
Grandy's bespoke designs have received global attention, including on the pages of Vogue U.K. and Forbes U.K., as well as on the red carpet at the Academy Awards and Cannes Film Festival.


Meal delivery subscriptions provide a great alternative to restaurant dining or takeout for those days when you just prefer a wholesome at-home meal made from scratch. It's also a great way to try new recipes and saves time on shopping for individual ingredients, which let's face it, can be a huge hassle in NYC. Ingredients come pre-portioned with easy to follow recipe cards and how-to videos, so all you do is come home and enjoy preparing a relaxing meal after a long day.
Blue Apron, the originator of the American food-box craze, allows you to experiment with foods you may otherwise not think to make on your own. The creative recipes from this culinary magnate incorporate rare ingredients to create amazing dishes like Tokyo-style Ramen noodles made from scratch, fresh wonton noodles, seared cod and creme fraiche sauce, and more. The weekly subscription includes access to a 2-person or 4-person family plan, starting at just under $60 and $70, respectively. You can even add a monthly wine subscription made to pair with your dinner entrees.
If you're looking for a meal kit that accommodates a vegan lifestyle, try plant-based service Purple Carrot.
Hamptons Lane sources high-quality hand-picked artisan ingredients, serving ware, and kitchen tools to help chefs, entertainers, and food lovers from all over enhance their cooking experience. Select from monthly themed boxes, like The Pasta Box, Rustic Italian, Indian Cuisine, Clean Eating, Fondue Party, Crepes, and more for just under $50 for a monthly subscription.
If you're into the organic food movement, then Sun Basket won't disappoint. This service buys its ingredients entirely from USDA-approved sources to ensure that your meals are 100% hormone-, pesticide-, GMO-, and antibiotic-free. Order the classic plan, which provides 3 meals for 2 or 4 people, or the family plan which feeds a family of four. For additional details, promotions, and FAQs see www.boxedmealz.com/sun-basket.
Chef'd features meal plans curated from famous chefs, including NY Times food writers, allrecipes.com, Fabio Viviani, Atkins, and more, which is just perfect for the seasoned chef, or those who just want to cook like one. Simply select your recipe from the a la carte menu, and the ingredients will be shipped to you, no subscription required. Chef'd also has a Spoon University Meal Plan which delivers meals and snacks to hungry college students.
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Purple Carrot is a plant-based meal delivery plan that caters specifically to vegans, with inventive, easy-to-prep meals for two, three, or four. Dish up recipes like Thai tofu salads, black bean kale bowls, seared scallops with gold beet-citrus salsa and Yukon mash. Purple Carrot also worked with famed NFL player Tom Brady to develop a line of high protein performance meals, featuring foods like cannellini bean burgers and sweet pepper pesto and smashed potatoes, and more. Opt for the 1-2 or 3-4-person plans starting at just under $70 and $74 a week, respectively.
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In , Amazon entered into a similar agreement with Borders Group , under which Amazon would comanage Borders. On October 18, , Amazon.
In November , Amazon announced a partnership with the United States Postal Service to begin delivering orders on Sundays. The service, included in Amazon's standard shipping rates, initiated in metropolitan areas of Los Angeles and New York because of the high-volume and inability to deliver in a timely way, with plans to expand into Dallas , Houston , New Orleans and Phoenix by In June , Nike confirmed a "pilot" partnership with Amazon to sell goods directly on the platform.
In November , Amazon reached an agreement with Apple Inc. As a result of this partnership, only Apple Authorized Resellers may sell Apple products on Amazon effective January 4, Amazon uses many different transportation services to deliver packages.
Amazon-branded services include:. As of December , it is not hiring delivery drivers as employees. The products can be purchased on the company's website or at over 50, bricks-and-mortar pharmacies in the United States.
Amazon owns over 40 subsidiaries, including Audible , Diapers. Amazon Maritime, Inc. Audible sells digital audiobooks , radio and television programs and audio versions of magazines and newspapers.
Through its production arm, Audible Studios, Audible has also become the world's largest producer of downloadable audiobooks. The deal closed in March and Audible became a subsidiary of Amazon.
Beijing Century Joyo Courier Services is a subsidiary of Amazon and it applied for a freight forwarding license with the US Maritime Commission.
Amazon is also building out its logistics in trucking and air freight to potentially compete with UPS and FedEx.
Brilliance Audio is an audiobook publisher founded in by Michael Snodgrass in Grand Haven , Michigan. In , Brilliance Audio invented a technique for recording twice as much on the same cassette.
It offers a selection of more than 40, comic books and graphic novels across Android, iOS, Fire OS and Windows 8 devices and over a web browser.
Amazon bought the company in April CreateSpace, which offers self-publishing services for independent content creators, publishers, film studios, and music labels, became a subsidiary in Eero, stylized as eero, is a company that manufactures mesh-capable routers.
The company was founded in and is based in San Francisco. Amazon announced it would buy Eero in Goodreads is a " social cataloging " website founded in December and launched in January by Otis Chandler, a software engineer, and entrepreneur, and Elizabeth Khuri.
The website allows individuals to freely search Goodreads' extensive user-populated database of books, annotations, and reviews. Users can sign up and register books to generate library catalogs and reading lists.
They can also create their own groups of book suggestions and discussions. Amazon bought the company in March In October , Amazon finalized the acquisition of Health Navigator, a startup developing APIs for online health services.
The startup will form part of Amazon Care, which is the company's employee healthcare service. Junglee is a former online shopping service provided by Amazon that enabled customers to search for products from online and offline retailers in India.
Junglee started off as a virtual database that was used to extract information from the Internet and deliver it to enterprise applications.
As it progressed, Junglee started to use its database technology to create a single window marketplace on the Internet by making every item from every supplier available for purchase.
Web shoppers could locate, compare and transact millions of products from across the Internet shopping mall through one window.
Amazon acquired Junglee in , and the website Junglee. It curated and enabled searching for a diverse variety of products such as clothing, electronics, toys, jewelry and video games, among others, across thousands of online and offline sellers.
Millions of products are browsable, the client selects a price, and then they are directed to a seller. In November , Amazon closed down Junglee.
Kuiper Systems LLC, is a subsidiary of Amazon, set up to deploy a broadband satellite internet constellation with an announced 3, Low Earth orbit satellites to provide satellite based Internet connectivity.
PillPack is an online pharmacy specializing in shipping pre-sorted medications in by-day packets. It was acquired by Amazon in June, Lab, developers of integrated consumer electronics such as the Kindle , became a subsidiary in Ring is a home automation company founded by Jamie Siminoff in It is primarily known for its WiFi powered smart doorbells , but manufactures other devices such as security cameras.
Shelfari was a social cataloging website for books. Shelfari users built virtual bookshelves of the titles which they owned or had read and they could rate, review, tag and discuss their books.
Users could also create groups that other members could join, create discussions and talk about books, or other topics. Recommendations could be sent to friends on the site for what books to read.
Amazon bought the company in August On March 28, , Amazon confirmed it would be acquiring Souq. Twitch is a live streaming platform for video, primarily oriented towards video gaming content.
The service was first established as a spin-off of a general-interest streaming service known as Justin. Its prominence was eclipsed by that of Twitch, and Justin.
The site's rapid growth had been boosted primarily by the prominence of major esports competitions on the service, leading GameSpot senior esports editor Rod Breslau to have described the service as "the ESPN of esports".
On August 10, , Amazon announced the rebranding of Twitch Prime , the live-streaming site, renaming it Prime Gaming [1] in another attempt to crack the video game market after failing a big-budget game effort.
With Twitch Prime, users will be given a free subscription to Twitch, with free games from small studios and discounts for larger titles like Grand Theft Auto and League of Legends.
On 2 November , Twitch announced a virtual flagship conference and named it GlitchCon instead of TwitchCon to be held on November The main aim of the conference will be to bring its numerous, disparate communities of streamers and fans together where they can be real life confidants.
Whole Foods Market is an American supermarket chain exclusively featuring foods without artificial preservatives, colors, flavors, sweeteners, and hydrogenated fats.
On August 23, , it was reported that the Federal Trade Commission approved the merger between Amazon. Amazon first launched its distribution network in with two fulfillment centers in Seattle and New Castle , Delaware.
Amazon has several types of distribution facilities consisting of crossdock centers, fulfillment centers, sortation centers, delivery stations, Prime now hubs, and Prime air hubs.
There are 75 fulfillment centers and 25 sortation centers with over , employees. A computer that records the location of goods and maps out routes for pickers plays a key role: employees carry hand-held computers which communicate with the central computer and monitor their rate of progress.
Some warehouses are partially automated with systems built by Amazon Robotics. Amazon fulfillment center in Macon , Georgia, U. The domain amazon.
Results generated by Amazon's search engine are partly determined by promotional fees. Amazon allows users to submit reviews to the web page of each product.
Reviewers must rate the product on a rating scale from one to five stars. Amazon provides a badging option for reviewers which indicate the real name of the reviewer based on confirmation of a credit card account or which indicate that the reviewer is one of the top reviewers by popularity.
Customers may comment or vote on the reviews, indicating whether they found a review helpful to them. If a review is given enough "helpful" hits, it appears on the front page of the product.
In , Amazon was reported as being the largest single source of Internet consumer reviews. When publishers asked Bezos why Amazon would publish negative reviews, he defended the practice by claiming that Amazon.
There have been cases of positive reviews being written and posted by public relations companies on behalf of their clients [] and instances of writers using pseudonyms to leave negative reviews of their rivals' works.
Amazon has cooperated with around publishers to allow users to perform these searches. To avoid copyright violations, Amazon does not return the computer-readable text of the book.
Instead, it returns a picture of the matching page, instructs the web browser to disable printing and puts limits on the number of pages in a book a single user can access.
Additionally, customers can purchase online access to some of the same books via the "Amazon Upgrade" program. Worldwide, Amazon has "over , members" in its affiliate programs.
Unlike eBay , Amazon sellers do not have to maintain separate payment accounts; all payments are handled by Amazon.
Associates can access the Amazon catalog directly on their websites by using the Amazon Web Services AWS XML service.
A new affiliate product, aStore, allows Associates to embed a subset of Amazon products within another website, or linked to another website.
In June , Amazon Seller Product Suggestions was launched rumored to be internally called "Project Genesis" to provide more transparency to sellers by recommending specific products to third-party sellers to sell on Amazon.
Products suggested are based on customers' browsing history. In July the 3rd U. City Court of Appeals in Philadelphia ruled that Amazon can be held accountable for faulty third-party sales.
Heather Oberdorf had sued the company in over a dog leash that snapped, causing permanent loss of vision in one eye.
If upheld, the decision would expose Amazon and similar platform businesses to strict liability lawsuits for defective products, which represents a major change in the law.
The Amazon sales rank ASR provides an indication of the popularity of a product sold on any Amazon locale.
It is a relative indicator of popularity that is updated hourly. Effectively, it is a "best sellers list" for the millions of products stocked by Amazon.
In particular, products that experience large jumps up or down in their sales ranks may be included within Amazon's lists of "movers and shakers"; such a listing provides additional exposure that might lead to an increase in sales.
However, Amazon has now begun to release point of sale data via the Nielsen BookScan service to verified authors. Some companies have analyzed Amazon sales data to generate sales estimates based on the ASR, [] though Amazon states:.
Please keep in mind that our sales rank figures are simply meant to be a guide of general interest for the customer and not definitive sales information for publishers—we assume you have this information regularly from your distribution sources.
Amazon employs a multi-level e-commerce strategy. Amazon started by focusing on business-to-consumer relationships between itself and its customers and business-to-business relationships between itself and its suppliers and then moved to facilitate customer-to-customer with the Amazon marketplace which acts as an intermediary to facilitate transactions.
The company lets anyone sell nearly anything using its platform. In addition to an affiliate program that lets anyone post Amazon links and earn a commission on click-through sales, there is now a program which lets those affiliates build entire websites based on Amazon's platform.
Some other large e-commerce sellers use Amazon to sell their products in addition to selling them through their own websites. The sales are processed through Amazon.
Small sellers of used and new goods go to Amazon Marketplace to offer goods at a fixed price. In November , Amazon opened a physical Amazon Books store in University Village in Seattle.
The store is 5, square feet and prices for all products match those on its website. In June , it was reported that Amazon planned to open brick and mortar bookstores in Germany.
In September , Amazon launched Luxury Stores on its mobile app, where Oscar de la Renta become the first and only label to partner with the firm.
Since sales increased from Since its founding, the company has attracted criticism and controversy for its actions, including: supplying law enforcement with facial recognition surveillance tools; [] forming cloud computing partnerships with the CIA ; [] leading customers away from bookshops; [] adversely impacting the environment; [] placing a low priority on warehouse conditions for workers; actively opposing unionization efforts; [] remotely deleting content purchased by Amazon Kindle users; taking public subsidies; seeking to patent its 1-Click technology; engaging in anti-competitive actions and price discrimination ; [29] [30] and reclassifying LGBT books as adult content.
In December , Amazon faced a backlash from small businesses for running a one-day deal to promote its new Price Check app. One effort to squeeze the most vulnerable book publishers was known within the company as the Gazelle Project, after Bezos suggested, according to Brad Stone , "that Amazon should approach these small publishers the way a cheetah would pursue a sickly gazelle.
In , Amazon emitted In September , Amazon workers organized a walk-out as part of the Global Climate Strike.
That said, Amazon's CEO has also signed the Climate Pledge, in which Amazon would meet the Paris climate agreement goals 10 years ahead of schedule, and would be carbon-neutral by Besides this pledge, it also ordered electric delivery trucks from Rivian.
Amazon funds both climate denial groups including the Competitive Enterprise Institute and politicians denying climate change including Jim Inhofe.
Construction has been suspended while these matters are decided. Amazon considered making an option for Prime customers to have packages delivered at the most efficient and environmentally-friendly time allowing the company to combine shipments with the same destination but decided against it out of fear customers might reduce purchases.
The selling of counterfeit products by Amazon has attracted widespread notice, with both purchases marked as being fulfilled by third parties and those shipped directly from Amazon warehouses being found to be counterfeit.
This has included some products sold directly by Amazon itself and marked as "ships from and sold by Amazon. One Amazon business practice that encourages counterfeiting is that, by default, seller accounts on Amazon are set to use "commingled inventory".
With this practice, the goods that a seller sends to Amazon are mixed with those of the producer of the product and with those of all other sellers that supply what is supposed to be the same product.
In June , Buzzfeed reported that some products identified on the site as "Amazon's choice" were low quality, had a history of customer complaints, and exhibited evidence of product review manipulation.
In August , The Wall Street Journal reported that they had found more than 4, items for sale on Amazon's site that had been declared unsafe by federal agencies, had misleading labels, or had been banned by federal regulators.
In the wake of the WSJ investigation, three U. The letter said that "Unquestionably, Amazon is falling short of its commitment to keeping safe those consumers who use its massive platform.
In December , The Wall Street Journal reported that some people were literally retrieving trash out of dumpsters and selling it as new products on Amazon.
The reporters ran an experiment and determined that it was easy for a seller to set up an account and sell cleaned up junk as new products.
In addition to trash, sellers were obtaining inventory from clearance bins, thrift stores, and pawn shops. In August , an appeals court in California ruled that Amazon can be held liable for unsafe products sold on its website.
A California woman had bought a replacement laptop battery that caught fire and caused her to receive third-degree burns. Amazon's state sales tax collection policy has changed over the years since it did not collect any sales taxes in its early years.
In the U. In most countries where Amazon operates, a sales tax or value added tax is uniform throughout the country, and Amazon is obliged to collect it from all customers.
Proponents of forcing Amazon. Many U. Amazon paid no federal income taxes in the U. In early , President Donald Trump repeatedly criticized Amazon's use of the United States Postal Service and its prices for the delivery of packages, stating, "I am right about Amazon costing the United States Post Office massive amounts of money for being their Delivery Boy," Trump tweeted.
Shepard Smith of Fox News disputed Trump's claims and pointed to evidence that the USPS was offering below-market prices to all customers with no advantage to Amazon.
However, analyst Tom Forte pointed to the fact that Amazon's payments to the USPS are not made public and that their contract has a reputation for being "a sweetheart deal".
Throughout the summer of , Vermont Senator Bernie Sanders criticized Amazon's wages and working conditions in a series of YouTube videos and media appearances.
He also pointed to the fact that Amazon had paid no federal income tax in the previous year. The statement also charged that it was inappropriate for him to refer to SNAP as "food stamps".
Sanders congratulated the company for making this decision. Amazon has opposed efforts by trade unions to organize in both the United States and the United Kingdom.
In , employees in Seattle were laid off by Amazon. The Washington Alliance of Technological Workers WashTech accused the company of violating union laws, and claimed Amazon managers subjected them to intimidation and heavy propaganda.
Amazon denied any link between the unionization effort and layoffs. It was alleged that the company victimized or sacked four union members during the recognition drive and held a series of captive meetings with employees.
An Amazon training video that was leaked in stated "We are not anti-union, but we are not neutral either.
We do not believe unions are in the best interest of our customers or shareholders or most importantly, our associates. Factors including racial diversity, proximity to other unions, poverty levels in the surrounding community and calls to the National Labor Relations Board were named as contributors to "unionization risk".
In early , an Amazon internal documents were leaked, it said that Whole Foods has been using an interactive heat map to monitor its locations across the U.
Data collected in the heat map suggest that stores with low racial and ethnic diversity, especially those located in poor communities, are more likely to unionize.
Former employees, current employees, the media, and politicians have criticized Amazon for poor working conditions at the company.
As a result of these inhumane conditions, employees became extremely uncomfortable and suffered from dehydration and collapse.
Loading-bay doors were not opened to allow in fresh air because of concerns over theft. Some workers, "pickers", who travel the building with a trolley and a handheld scanner "picking" customer orders can walk up to 15 miles 24 kilometres during their workday and if they fall behind on their targets, they can be reprimanded.
The handheld scanners give real-time information to the employee on how quickly or slowly they are working; the scanners also serve to allow Team Leads and Area Managers to track the specific locations of employees and how much "idle time" they gain when not working.
In a German television report broadcast in February , journalists Diana Löbl and Peter Onneken conducted a covert investigation at the distribution center of Amazon in the town of Bad Hersfeld in the German state of Hessen.
The report highlights the behavior of some of the security guards, themselves being employed by a third party company, who apparently either had a neo-Nazi background or deliberately dressed in neo-Nazi apparel and who were intimidating foreign and temporary female workers at its distribution centers.
The third party security company involved was delisted by Amazon as a business contact shortly after that report.
In March , it was reported in The Verge that Amazon would be removing non-compete clauses of 18 months in length from its US employment contracts for hourly-paid workers, after criticism that it was acting unreasonably in preventing such employees from finding other work.
Even short-term temporary workers have to sign contracts that prohibit them from working at any company where they would "directly or indirectly" support any good or service that competes with those they helped support at Amazon, for 18 months after leaving Amazon, even if they are fired or made redundant.
A front-page article in The New York Times profiled several former Amazon employees [] who together described a "bruising" workplace culture in which workers with illness or other personal crises were pushed out or unfairly evaluated.
In an effort to boost employee morale, on November 2, , Amazon announced that it would be extending six weeks of paid leave for new mothers and fathers.
This change includes birth parents and adoptive parents and can be applied in conjunction with existing maternity leave and medical leave for new mothers.
In mid, investigations by journalists and media outlets such as The Guardian reported poor working conditions at Amazon's fulfillment centers.
On Black Friday , Amazon warehouse workers in several European countries, including Italy, Germany, Spain and the United Kingdom, went on strike to protest inhumane working conditions and low pay.
The Daily Beast reported in March that emergency services responded to calls from 46 Amazon warehouses in 17 states between the years and , all relating to suicidal employees.
The workers attributed their mental breakdowns to employer-imposed social isolation, aggressive surveillance, and the hurried and dangerous working conditions at these fulfillment centers.
One former employee told The Daily Beast "It's this isolating colony of hell where people having breakdowns is a regular occurrence.
On July 15, , during the onset of Amazon's "Prime Day" sale event, Amazon employees working in the United States and Germany went on strike in protest of unfair wages and poor working conditions.
In March , during the coronavirus outbreak when the government instructed companies to restrict social contact, Amazon's UK staff was forced to work overtime to meet the demand spiked by the disease.
A GMB spokesperson said the company had put "profit before safety". In August , BBC reported on Amazon's Twitter ambassadors.
Their constant support for and defense of Amazon and its practices have led many Twitter users to suspect that they are in fact bots , being used to dismiss the issues effecting Amazon workers.
In its statement to its US shareholders, Amazon stated that "we respect and support the Core Conventions of the International Labour Organization ILO , the ILO Declaration on Fundamental Principles and Rights at Work , and the United Nations Universal Declaration of Human Rights ".
Operation of these Global Human Rights Principles has been "long-held at Amazon, and codifying them demonstrates our support for fundamental human rights and the dignity of workers everywhere we operate".
On 27 November , Amnesty International said, workers in working for Amazon have faced great health and safety risks since the start of the COVID pandemic.
On Black Friday , one of Amazon's busiest periods, company failed to ensure the key safety features in France , Poland , the United Kingdom and USA.
Workers have been risking their health and lives to ensure essential goods are delivered to consumer doorsteps, helping Amazon achieve record profits.
On January 24, , Amazon said that it was planning to open a pop-up clinic hosted in partnership with Virginia Mason Franciscan Health in Seattle in order to vaccinate 2, persons against COVID on the first day.
Department of Defense. In May , Amazon threatened the Seattle City Council over an employee head tax proposal that would have funded houselessness services and low-income housing.
Although originally passed, the measure was soon repealed after an expensive repeal campaign spearheaded by Amazon. The incentives given by the Metropolitan Council of Nashville and Davidson County to Amazon for their new Operations Center of Excellence in Nashville Yards , a site owned by developer Southwest Value Partners , have been controversial, including the decision by the Tennessee Department of Economic and Community Development to keep the full extent of the agreement secret.
The Tennessee Coalition for Open Government called for more transparency. While Amazon has publicly opposed secret government surveillance, as revealed by Freedom of Information Act requests it has supplied facial recognition support to law enforcement in the form of the Rekognition technology and consulting services.
Initial testing included the city of Orlando , Florida, and Washington County , Oregon. Amazon offered to connect Washington County with other Amazon government customers interested in Rekognition and a body camera manufacturer.
These ventures are opposed by a coalition of civil rights groups with concern that they could lead to an expansion of surveillance and be prone to abuse.
Specifically, it could automate the identification and tracking of anyone, particularly in the context of potential police body camera integration.
The UK government awarded Amazon a contract that gives the company free access to information about healthcare published by the UK's National Health Service.
The material, which excludes patient data, could also allow the company to make, advertise and sell its own products.
The contract allows Amazon access to information on symptoms, causes and definitions of conditions, and "all related copyrightable content and data and other materials".
The company can also share the information with third parties. The government said that allowing Alexa devices to offer expert health advice to users will reduce pressure on doctors and pharmacists.
On February 17, , a Panorama documentary highlighted the amount of data collected by the company and the move into surveillance causing concerns of politicians and regulators in the US and Europe.
On June 11, , the European Union announced that it will be pressing charges against Amazon over its treatment of third-party e-commerce sellers.
In July , Amazon along with other tech giants Apple , Google and Facebook were accused of maintaining harmful power and anti-competitive strategies to quash potential competitors in the market.
House Antitrust Subcommittee. House of Representatives released a report accusing Amazon of abusing a monopoly position in ecommerce to unfairly compete with sellers on its own platform.
Anti-vaccination and non evidence-based cancer 'cures' have routinely appeared high in Amazon's books and videos.
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HTC 10 vs HTC One M9
What's the difference between HTC's newest phone and its predecessor?
by: Adam Shepherd
One of the Android family's stalwarts, HTC has consistently been among the most popular smartphone brands.
It's somewhat fallen out of favour in recent years, but the company is betting on the new HTC 10 to help its reclaim its place as the kings of the Android hill.
Design and casing
The 10 still has a curved back likes its One M-series predecessors, but it's now offset by a deep rear chamfer that really sets it apart, both from its predecessors and its rivals. It's also eschewed the brushed-aluminium finish, opting instead for a semi-gloss backing.
Elsewhere, the screen size has been bumped to 5.2in as opposed to the M9's flat 5in measurement, but the bezels appear to have shrunk, meaning that there shouldn't be a notable increase in footprint.
HTC has also upped the resolution for the new 10, fitting it with a 2K QHD 2560x1440 pixel screen. While this may sound impressive, it's in the same ballpark as 1080p displays in terms of sharpness. It should have a high degree of colour accuracy over the M9.
Other behind-the-scenes elements have been tweaked too. The latency of the touchscreen has been reduced, which should make it feel more responsive, and the HTC 10 has also gone back to capacitive physical buttons, rather than the M9's software equivalents.
Performance and Storage
As expected, the HTC 10 keeps pace with current-gen flagships in terms of the latest components. It has 4GB of RAM and a Snapdragon 820 CPU. Both phones also have 32GB of internal storage.
The M9's 3GB allocation and Snapdragon 810 chip is by no means slow, but the HTC 10 should be more than enough to run demanding apps for some time to come. We'll know more once we can put it through our suite of benchmarks, however.
Equipped with a 3,000mAH battery, HTC claims that the 10 can last a full two days thanks to its oddly-named PowerBotics efficiency technology.
The company is touting 27 hours of 3G talk time, 73 hours of audio playback, or 13 hours of web browsing which, if accurate, would be an improvement over what the M9's 2,840mAh cell provides.
In addition to this, the M9's QuickCharge functionality has been upgraded from 2.0 to 3.0. Where 30 minutes of charging would provide the M9 with around 60 per cent battery, HTC now claims that the same charge time will power the 10 for an entire day.
The HTC 10 uses the increasingly common USB Type C standard instead of the M9's older but more common micro USB, and includes a QuickCharge-compatible charger in the box.
Like many companies, HTC appears to be betting big on camera improvements with the 10. The quality of both front and rear shooters has been improved substantially, and the 10 could now prove a serious rival to the major heavyweights.
The HTC 10's Ultrapixel 2 camera comes with a larger f/1.8 aperture, up from f/2.2 on the M9, and allegedly has improved optical image stabilization.
Autofocus has also been upgraded. The second-generation laser autofocus has double the range of the previous version, and has an alleged time of just 0.2 seconds, as well as smoother transitions.
Enhanced manual controls and support for capturing RAW files have been added, which is sure to please keen photographers, and the UI in general has been overhauled to be smoother and more polished.
In fact, according to camera benchmark DxOMark, the HTC 10's snapper is tied with the mightily impressive Galaxy S7, which is no mean feat.
It's not just good news for photography bods, either; the HTC 10's five megapixel front-facing camera has also been given some love. It's got OIS - rarely seen on selfie and video conferencing cameras - and a f/1.8 aperture, making it a marked improvement over the M9's offering.
HTC has put a lot of effort into refining its Sense UI overlay, bringing it much more in line with Google's Material Design. The company has worked directly with Google to "reboot the Android experience".
Duplicate apps have been eliminated, meaning you won't have to choose between two stock music or gallery apps, for example. Some will be Google's default variants, but some will be HTC's own-brand offerings.
The layout of apps can also be customized. Icons and shortcuts can be set to any size, and placed wherever you like, irrespective of the traditional grid format.
As standard for flagship devices, the HTC 10 comes complete with a fingerprint sensor. It's mounted in the Home button. The sensor can unlock the device in just 0.2 seconds, but also features application unlocking, for an added level of security.
Sadly, HTC's front-facing BoomSound speakers have been dropped in favour of dual speakers - a tweeter at the top, and bottom-mounted 'subwoofer', each with its own amplifier.
On the other hand, the HTC Connect utility for streaming speaker audio now features native support for Apple's AirPlay, which means you should be able to cast audio directly to your AirPlay-enabled HiFi equipment.
The MicroSD slot can accept cards up to a maximum of 2TB in capacity, although no MicroSD cards are that big yet.
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