Litigating Artificial Intelligence: When Does AI Violate Our Legal Rights? Read full article May 27, 2021, 3:20 PM ·3 min read From the minds of Canada's leading law and technology experts comes a playbook for understanding the multi-faceted intersection of AI and the law TORONTO, May 27, 2021 (GLOBE NEWSWIRE) -- We are living in an Artificial Intelligence (AI) boom. Self-driving cars, personal voice assistants, and facial recognition technology are just a few of the AI-enabled technologies permeating into everyday life. But what happens when AI causes harm or violates our rights? If your self-driving car gets into an accident while on autopilot, are you responsible? Emond Publishing, Canada's leading independent legal publisher, today announced the release of Litigating Artificial Intelligence, a book examining AI-informed legal determinations, AI-based lawsuits, and AI-enabled litigation tools. Anchored by the expertise of general editors Jill R. Presser, Jesse Beatson, and Gerald Chan, this title offers practical insights regarding AI's decision-making capabilities, position in evidence law and product-based lawsuits, role in automating legal work, and use by the courts, tribunals, and government agencies. For example, can government agencies use AI-powered facial recognition software to identify BLM protestors and Capitol rioters, or does this violate privacy rights? Who is liable, users, developers, or AI? What laws are in place to prevent AI-related crimes, and how do litigators prosecute the responsible parties?

Its platform uses computer vision and artificial intelligence technologies, along with mobile phone cameras and small drones, to develop what it calls …

Most stock pickers have one goal: to beat the market. Since January 2015, the S&P 500 has returned an average 13% per year, or 110% total. That's not bad, but it pales in comparison to NVIDIA's (NASDAQ:NVDA) 3,410% return over the same period. Given the chipmaker's $438 billion market cap, investors may think it's too late to buy this stock. But NVIDIA recently delivered strong first-quarter results, reminding Wall Street that it's still a growth company.

Verbit today announced the close of a $157 million series D round the company says will bolster its product R&D and hiring efforts. CEO Tom Livne, who noted that the raise brings the company's post-money valuation to more than $1 billion, said the capital will also support Verbit's geographic expansion as it prepares for an initial public offering. The voice and speech recognition tech market is anticipated to be worth $31.82 billion by 2025, driven by new applications in the banking, health care, and automotive industries. In fact, it's estimated that one in five people in the U.S. interacts with a smart speaker on a daily basis and that the share of Google searches conducted by voice in the country recently surpassed 30%. Livne, who cofounded Verbit.ai with Eric Shellef and Kobi Ben Tzvi in 2017, asserts that the New York-based startup will contribute substantially to the voice transcription segment's rise.

There is often confusion between artificial intelligence (AI) and machine learning (ML), but there are differences. AI, for example, is a broad description of the category of technologies that allow for the simulation of human-like capabilities in machines. Machine learning, meanwhile, is a subset of AI. It generally involves the processing of large amounts of data, which is then applied to algorithms. By doing this, ML makes it possible for a computer system to recognize objects, predict when a machine will fail, or even drive a car. In other words, it allows systems to learn and make choices with little human interaction.

GitLab announced this week it has acquired UnReview, a provider of a tool that employs machine learning algorithms to both identify which expert code reviewers to assign to a project based on the quality of their previous efforts and current workloads. David DeSanto, senior director for product management at GitLab, said the acquisition of UnReview is the latest step in an AI strategy that, in addition to optimizing DevOps processes, will also eventually unify machine learning operations (MLOps) and DevOps workflows. Accessed via the Dev section of the GitLab platform, UnReview will also be employed to manage the overall code review process. DeSanto said GitLab is committed to employing AI technologies to automate workflows and compressing cycle times across all stages of the DevSecOps life cycle. The goal is to not eliminate the need for DevOps teams but rather eliminate low-level tasks that conspire to hamper productivity, while at the same time improving application security, noted DeSanto.

Let's see why these giants of industry (and pandemic profits) are circulating in investors' portfolios. Q.ai runs daily factor models to get the most up-to-date reading on stocks and ETFs. Our deep-learning algorithms use Artificial Intelligence (AI) technology to provide an in-depth, intelligence-based look at a company – so you don't have to do the digging yourself. Sign up for the free Forbes AI Investor newsletter here to join an exclusive AI investing community and get premium investing ideas before markets open. Netflix, Inc NFLX ticked up 0.2% on Wednesday to $502.36 per share, ending the day with 2.46 million trades.

They have to strike a balance between maintaining top-line revenue growth and managing sustainable profit margins. The reason why the task becomes difficult is because they have to do so while managing a dynamic set of operations. Moreover, a shift in consumer preferences, advances in data & analytics, channel shifts, and pandemic-led disruptions have created new challenges for retail and CPG companies. However, in the current market scenario, they also have the opportunity to upgrade RGM, thereby creating equilibrium between growth and efficiency. They can increase the use of complex and action-oriented analytics across the product catalogue, optimize value capture approaches, use automated technology, and partner with retailers for shared value creation. Competitiveness has considerably intensified within the CPG industry.

A pandemic-fueled run on computers helped HP Inc. and Dell Technologies Inc. deliver strong financial results for the latest quarter despite a semiconductor shortage that is denting some industries. Dell on Thursday reported that first-quarter revenue rose 12% to $24.5 billion from a year earlier driven by a 42% jump in consumer revenue within the client solutions group that includes desktops and notebooks. The strong start to its business year comes after Dell, in February, reported record full-year revenue. Personal-computer sales registered their strongest growth in a decade last year, underscoring a shift from mobile devices brought on by the coronavirus pandemic, according to industry data. PC shipments overall rose 13% in 2020 and are expected to increase 18% in 2021 despite the semiconductor shortage, according to International Data Corp. "We continue to see very strong demand on the consumer side, and the demand on the commercial side is also starting to strengthen as offices reopen," said HP Chief Executive Enrique Lores.

Semiconductor maker Nvidia (NASDAQ: NVDA) slipped in pre-market trade Thursday, following a better-than-expected earnings report for fiscal 2022's first quarter. Shares fell $2.70, or 0.43%, to $625.30 The company, which specializes in graphics chips, earned $3.66 per share on revenue of $5.66 billion. Wall Street had pegged net income at $3.28 a share on revenue of $5.41 billion. Those results marked year-over-year gains of 103% and 84%, respectively.