A joint research collaboration between US universities and IBM has formulated a proof-of-concept adversarial attack that's theoretically capable of causing stock market losses, simply by changing one word in a retweet of a Twitter post. In one experiment, the researchers were able to hobble the Stocknet prediction model with two methods: a manipulation attack and a concatenation attack. The attack surface for an adversarial attack on automated and machine learning stock prediction systems is that a growing number of them are relying on organic social media as predictors of performance; and that manipulating this'in-the-wild' data is a process that can, potentially, be reliably formulated. Besides Twitter, systems of this nature ingest data from Reddit, StockTwits, and Yahoo News, among others. The difference between Twitter and the other sources is that retweets are editable, even if the original tweets are not.
We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. The past 12 months have taught us that the metaverse is regarded by many as the next major frontier for tech. The furor caused by Facebook's conspicuous rebranding to Meta has shown that the 21st century's biggest technological space race will be fought on the battlegrounds of Wall Street -- but the stock market has also helped to identify some of the forgotten players that will be integral to the mechanics of this brave new world. The race for the metaverse is a unique prospect for the 21st century, primarily because there is little understanding of what such a revolutionary mixed reality digital space will actually look like in practice -- or how businesses will be looking to capitalize on the new technology. So, who will succeed in profiting the most from the metaverse?
It was undoubtedly one of the outperformers in the first month of the current stock market year. The shares of the Australian company BrainChip Holdings, which also has subsidiaries in the US, India and France, almost quadrupled from AUD 0.71 to AUD 2.25 within one month. The announcement that Mercedes intends to develop systems based on BrainChip's Akida hardware and software caused a veritable buying panic. Among other things, the technology makes the "Hey, Mercedes" voice control in the EQXX five to ten times more efficient than conventional voice control. Since February, the stock has been in a strong consolidation phase, which is not unusual for such an innovative technology company.
Artificial intelligence in businesssimply involves the use ofintelligentcomputer software with human-like capabilities to boost revenue, improve customer experience, increase productivity and efficiency, and drivebusinessgrowth and transformation. The global Artificial Intelligence in Business market was valued at million in 2021 and is projected to reach US$ million by 2028, at a CAGR of % during the forecast period. The U.S. Market is Estimated at $ Million in 2021, While China is Forecast to Reach $ Million by 2028. The global key manufacturers of Artificial Intelligence in Business include Google, Microsoft, IBM, Amazon Web Services, Nuance, Verint, DataRobot, SAS and MathWorks, etc. In 2021, the global top five players have a share approximately % in terms of revenue.
Edition: 6; Released: February 2022 Executive Pool: 133782 Companies: 202 - Players covered include ABB; Alphabet Inc. (Google Inc.); Amazon; Asustek Computer; Blue Frog Robotics; Bsh HausgerÃ¤te; Fanuc; Hanson Robotics; Harman International Industries; IBM Corporation; Intel Corporation; Jibo; Kuka; LG; Mayfield Robotics; Microsoft Corporation; Neurala; Nvidia; Promobot; Softbank; Xilinx and Others. Coverage: All major geographies and key segments Segments: Component (Software, Hardware); Robot Type (Service, Industrial); Application (Military & Defense, Law Enforcement, Personal Assistance & Caregiving, Public Relations, Education & Entertainment, Industrial, Stock Management, Other Applications) Geographies: World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World. Complimentary Project Preview - This is an ongoing global program. Preview our research program before you make a purchase decision. We are offering a complimentary access to qualified executives driving strategy, business development, sales & marketing, and product management roles at featured companies.
This special issue interrogates the meaning and impacts of "tech ethics": the embedding of ethics into digital technology research, development, use, and governance. In response to concerns about the social harms associated with digital technologies, many individuals and institutions have articulated the need for a greater emphasis on ethics in digital technology. Yet as more groups embrace the concept of ethics, critical discourses have emerged questioning whose ethics are being centered, whether "ethics" is the appropriate frame for improving technology, and what it means to develop "ethical" technology in practice. This interdisciplinary issue takes up these questions, interrogating the relationships among ethics, technology, and society in action. This special issue engages with the normative and contested notions of ethics itself, how ethics has been integrated with technology across domains, and potential paths forward to support more just and egalitarian technology. Rather than starting from philosophical theories, the authors in this issue orient their articles around the real-world discourses and impacts of tech ethics--i.e., tech ethics in action.
Thinking artificial intelligence could boost your portfolio right about now? But which AI stocks beyond the usual suspects: Alphabet Inc. (NASDAQ: GOOG), Apple Inc. (NASDAQ: AAPL), Twilio Inc. (NYSE: TWLO), ServiceNow, Inc. (NYSE: NOW), NVIDIA Corporation (NASDAQ: NVDA) and QUALCOMM Incorporated (NASDAQ: QCOM). Whether you believe some of the famous companies above are bearish and/or overvalued (another argument for another day) or are just looking to inject some new blood into your portfolio, let's go through some options you might consider. But first, in the interest of education, what are AI stocks and which ones should you consider right now? Let's find out. At its most basic level, artificial intelligence (AI) refers to an algorithm or dynamic machine that learns and interprets the data given to it.
In this article, we discuss the 10 best AI stocks for 2022. If you want to skip our detailed analysis of these stocks, go directly to the 5 Best AI Stocks for 2022. Artificial intelligence is the backbone of a myriad of innovations in today's world such as self-driving cars, high-tech computing, enterprise solutions, and robotics to name a few. AI is also set to play a key role in blockchain technology which forms the basis of the cryptocurrency industry. In addition, AI also played a key role in fighting the spread of COVID-19 from contact tracing to robots and drone deployment to responding to urgent needs in hospitals as well as performing deliveries of food, medications, and equipment.
Sen, Jaydip, Mehtab, Sidra, Sen, Rajdeep, Dutta, Abhishek, Kherwa, Pooja, Ahmed, Saheel, Berry, Pranay, Khurana, Sahil, Singh, Sonali, Cadotte, David W. W, Anderson, David W., Ost, Kalum J., Akinbo, Racheal S., Daramola, Oladunni A., Lainjo, Bongs
Recent times are witnessing rapid development in machine learning algorithm systems, especially in reinforcement learning, natural language processing, computer and robot vision, image processing, speech, and emotional processing and understanding. In tune with the increasing importance and relevance of machine learning models, algorithms, and their applications, and with the emergence of more innovative uses cases of deep learning and artificial intelligence, the current volume presents a few innovative research works and their applications in real world, such as stock trading, medical and healthcare systems, and software automation. The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed. The volume will be useful for advanced graduate and doctoral students, researchers, faculty members of universities, practicing data scientists and data engineers, professionals, and consultants working on the broad areas of machine learning, deep learning, and artificial intelligence.