The stock market shook Wednesday after the Federal Reserve raised its inflation expectations for the year and moved up its next hike on interest rates. The policymaking Federal Open Market Committee noted that rate hikes may occur in 2023, a reversal from its March statements that it foresaw no increases until beyond then. However, a date for the Fed's expected reversal of its $120 billion per month bond buying program didn't come up, the Fed Chief has noted that the central bank will provide "advanced notice" before tapering asset purchases. This thrust investors' worries about fiscal policy decisions into the spotlight after weeks of nail-biting angst, while many individual stocks did indeed trend down for the day. But many of these stocks were already trending this week anyway on their own merits. Let's explore a few of them, and take a peek behind the curtain into what, exactly, is going on in some of America's biggest industries.
Tokyo stocks turned up Monday, getting a boost from a continued rally on Wall Street last week. The 225-issue Nikkei average of the Tokyo Stock Exchange rose 213.07 points, or 0.74%, to close at 29,161.80, The Topix index of all first section issues ended 5.73 points, or 0.29%, higher at 1,959.75, snapping its three-day losing streak. The Tokyo market got off to a strong start, after all three U.S. market gauges including the Dow Jones Industrial Average extended their gains Friday thanks to data showing improvement in consumer confidence in the United States in June. Although selling to lock in gains from the initial market spurt gathered steam in the morning, stocks gradually extended gains in the afternoon in pace with Dow futures in off-hours trading. Trading was generally lackluster with many players taking to the sidelines ahead of the U.S. Federal Reserve's two-day Federal Open Market Committee meeting from Tuesday, brokers said.
The direction of AI development is not preordained. It can be altered to increase human productivity, create jobs and shared prosperity, and protect and bolster democratic freedoms--if we modify our approach. The direction of AI development is not preordained. It can be altered to increase human productivity, create jobs and shared prosperity, and protect and bolster democratic freedoms--if we modify our approach. Artificial Intelligence (AI) is not likely to make humans redundant. Nor will it create superintelligence anytime soon. But like it or not, AI technologies and intelligent systems will make huge advances in the next two decades--revolutionizing medicine, entertainment, and transport; transforming jobs and markets; enabling many new products and tools; and vastly increasing the amount of information that governments and companies have about individuals. Should we cherish and look forward to these developments, or fear them? Current AI research is too narrowly focused on making advances in a limited set of domains and pays insufficient attention to its disruptive effects on the very fabric of society. There are reasons to be concerned. Current AI research is too narrowly focused on making advances in a limited set of domains and pays insufficient attention to its disruptive effects on the very fabric of society. If AI technology continues to develop along its current path, it is likely to create social upheaval for at least two reasons. For one, AI will affect the future of jobs. Our current trajectory automates work to an excessive degree while refusing to invest in human productivity; further advances will displace workers and fail to create new opportunities (and, in the process, miss out on AI's full potential to enhance productivity). For another, AI may undermine democracy and individual freedoms. Each of these directions is alarming, and the two together are ominous. Shared prosperity and democratic political participation do not just critically reinforce each other: they are the two backbones of our modern society.
Stock futures cut some losses last week on Thursday and Friday as markets rallied, but today looks like more of the same with selling pressure out of the early session. Inflation worries amid a massive corporate earnings quarter saw the S&P 500 fall as much as 4% last week, so if one thing is for sure, it is that volatility appears to be making a comeback. This week, we will get more information on how the Fed is feeling about inflation with the Fed minutes to be released Wednesday amid some massive consumer earnings cues from multinationals such as Walmart WMT, Home Depot HD, and Macy's M on Tuesday. For investors looking to find the best opportunities, the deep learning algorithms at Q.ai have crunched the data to give you a set of Top Buys. Our Artificial Intelligence ("AI") systems assessed each firm on parameters of Technicals, Growth, Low Volatility Momentum, and Quality Value to find the best Top Buys.
The study of the social impact of automated decision making has focused largely on issues of fairness at the point of decision, evaluating the fairness (with respect to a population) of a sequence or pipeline of decisions, or examining the dynamics of a game between the decision-maker and the decision subject. What is missing from this study is an examination of precarity: a term coined by Judith Butler to describe an unstable state of existence in which negative decisions can have ripple effects on one's well-being. Such ripple effects are not captured by changes in income or wealth alone or by one decision alone. To study precarity, we must reorient our frame of reference away from the decision-maker and towards the decision subject; away from aggregates of decisions over a population and towards aggregates of decisions (for an individual) over time. An individual who lives with higher precarity is more affected and less able to recover by the same negative decision than another with low precarity. Thus including only the direct impact of a single decision or a few decisions is insufficient to judge if that system was fair. However, precarity is not an attribute of an individual; it is a result of being subject to greater risks and fewer supports, in addition to starting off at a less secure position. Precarity is impacted by racism, sexism, ableism, heterosexism, and other systems of oppression, and an individual's intersectional identity may put one at greater risk in society, subject to a lower income for the same job, less able to build wealth even at the same income level, and less able to recover from harm.
In Yeshiva University's engineering-focused M.S. in Artificial Intelligence (AI), offered by the Katz School of Science and Health, students will learn the key skills most valued in today's marketplace, including machine learning and deep neural networks, along with cutting-edge technologies such as reinforcement learning, voice recognition and generation, and image recognition and generation. In the program's project-based courses, students will build systems, models and algorithms using the best available artificial intelligence design patterns and engineering principles, all done in the heart of Manhattan, a global epicenter for artificial intelligence work and research. Prof. Andrew Catlin is the program director for the AI program, with a background as a data scientist and production systems developer who has worked with such major clients as Fidelity Investments; Smart Money; Donaldson, Lufkin and Jenrette; Manufacturers Hanover Trust; and the National Football League. He is also a founder of multiple tech startups, including Hudson Technology and Metrics Reporting. He teaches graduate courses in recommender systems, natural language processing and neural networks, among others.
THE COFFEESHOP is an engine of social mobility. Barista jobs require soft skills and little experience, making them a first port of call for young people and immigrants looking for work. So it may be worrying that robotic baristas are spreading. RC Coffee, which bills itself "Canada's first robotic café", opened in Toronto last summer. "[T]he barista-to-customer interaction is somewhat risky despite people's best efforts to maintain a safe environment," the firm says.
This paper applies neural network models to forecast inflation. The use of a particular recurrent neural network, the long-short term memory model, or LSTM, that summarizes macroeconomic information into common components is a major contribution of the paper. Results from an exercise with US data indicate that the estimated neural nets usually present better forecasting performance than standard benchmarks, especially at long horizons. The LSTM in particular is found to outperform the traditional feed-forward network at long horizons, suggesting an advantage of the recurrent model in capturing the long-term trend of inflation. This finding can be rationalized by the so called long memory of the LSTM that incorporates relatively old information in the forecast as long as accuracy is improved, while economizing in the number of estimated parameters. Interestingly, the neural nets containing macroeconomic information capture well the features of inflation during and after the Great Recession, possibly indicating a role for nonlinearities and macro information in this episode. The estimated common components used in the forecast seem able to capture the business cycle dynamics, as well as information on prices.
Artificial intelligence salaries benefit from the perfect recipe for a sweet paycheck: a hot field and high demand for scarce talent. It's the ever-reliable law of supply and demand, and right now, anything artificial intelligence-related is in very high demand. According to Indeed.com, the average IT salary -- the keyword is "artificial intelligence engineer" -- in the San Francisco area ranges from approximately $134,135 per year for "software engineer" to $169,930 per year for "machine learning engineer." Check out our editorial recommendations on the best machine learning books. However, it can go much higher if you have the credentials firms need.
WASHINGTON (Reuters) - U.S. banking regulators announced on Monday they were soliciting public input on the growing use of artificial intelligence by financial institutions. In a joint statement, the regulators said they wanted feedback on the use of the technology by banks to police fraud, underwrite loans and for other purposes, and what perks and challenges it presents. The query was not connected to any specific regulatory project, but rather regulators said they were soliciting public comment to identify any areas where it may be helpful for agencies to clarify existing rules to address the use of AI. "The agencies support responsible innovation by financial institutions," the regulators said in the solicitation. "With appropriate governance, risk management, and compliance management, financial institutions' use of innovative technologies and techniques, such as those involving AI, has the potential to augment business decision-making, and enhance services available to consumers and businesses." The query from the Federal Reserve, Consumer Financial Protection Bureau, and other federal financial regulators underscores the growing prevalence of AI in the financial sector, what it could mean for lenders and borrowers alike.