The widespread disruption of AI is summed up best by Andrew Ng, the former chief scientist of Baidu, who views AI as the new electricity: "Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don't think AI will transform in the next several years." While most large corporations are undergoing technological transformations to use, support or offer AI technologies, the real magic takes place in the AI startup arena. According to CB Insights, the top 100 AI startups of 2017 have raised $11.7 billion in aggregate funding across 367 deals, thereby making the market rich with innovations plus financial backings. The most surprising AI startups and applications are those that are paving the way towards more unconventional verticals, such as insurance, background checks, real estate, health and retail. The unique application of AI in areas that aren't traditionally high-tech is particularly fascinating for multiple reasons.

Executives from Amazon, Apple, AT&T, Charter Communications, Google, and Twitter are heading to Washington Wednesday to testify before the Senate Commerce Committee on the topic of privacy. As ever, the main question will be: Are these companies doing enough to protect consumer privacy, and if not, what should Congress do about it? It has been the backdrop to just about every hearing with tech leaders over the last year--and there have been many. And yet, the threat of regulation carries new weight this time around. Over the summer, California passed the country's first data privacy bill, giving residents unprecedented control over their data.

In the summer of 1995, a second-year grad student called Sergey Brin was giving a tour of Stanford University to prospective students. Larry Page, an engineering graduate from the University of Michigan, was one of those being shown around the Palo Alto, California campus. "I thought he was pretty obnoxious," Larry Page said of the encounter. "He had really strong opinions about things, and I guess I did, too." "We both found each other obnoxious," said Sergey Brin.

Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

It is very important to adhere strictly to ethical and social influences when delivering most of our life to artificial intelligence systems. With industry 4.0, the internet of things, data analysis and automation have begun to be of great importance in our lives. With the Yapanese version of Industry 5.0, it has come to our attention that machine-human interaction and human intelligence are working in harmony with the cognitive computer. In this context, robots working on artificial intelligence algorithms co-ordinated with the development of technology have begun to enter our lives. But the consequences of the recent complaints of the Robots have been that important issues have arisen about how to be followed in terms of intellectual property and ethics. Although there are no laws regulating robots in our country at present, laws on robot ethics and rights abroad have entered into force. This means that it is important that we organize the necessary arrangements in the way that robots and artificial intelligence are so important in the new world order. In this study, it was aimed to examine the existing rules of machine and robot ethics and to set an example for the arrangements to be made in our country, and various discussions were given in this context.

This release contains "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, and Section 21E the Securities Exchange Act of 1934, as amended and such forward-looking statements are made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. Statements in this news release other than statements of historical fact are "forward-looking statements" that are based on current expectations and assumptions. Forward-looking statements involve risks and uncertainties that could cause actual results to differ materially from those expressed or implied by the statements, including, but not limited to, the following: the ability of On the Move Systems to provide for its obligations, to provide working capital needs from operating revenues, to obtain additional financing needed for any future acquisitions, to meet competitive challenges and technological changes, and other risks. On the Move Systems undertakes no duty to update any forward-looking statement(s) and/or to confirm the statement(s) to actual results or changes in On the Move Systems expectations.

Seven members of the US Congress have sent letters to the Federal Trade Commission (pdf), Federal Bureau of Investigation (pdf), and Equal Employment Opportunity Commission (pdf) asking whether the agencies have vetted the potential biases of artificial intelligence algorithms being used for commerce, surveillance, and hiring. "We are concerned by the mounting evidence that these technologies can perpetuate gender, racial, age, and other biases," a letter to the FTC says. "As a result, their use may violate civil rights laws and could be unfair and deceptive." The letters request that the agencies respond by the end of September with complaints they've received of unfair use of facial recognition or artificial intelligence, as well as details on how these algorithms are tested for fairness before being implemented by the government. In the letter to the EEOC, senators Kamala Harris, Patty Murray, and Elizabeth Warren specifically ask the agency to determine whether this technology could violate the Civil Rights Act of 1964, the Equal Pay Act of 1963, or the Americans with Disabilities Act of 1990.

RAD's suite of products which presently includes SCOT, WALLY and FRED provides recurring monthly revenue for RAD. On average, each SCOT, WALLY and FRED respectively can generate, over a 4 year period, $60,000, $25,000 and $12,000 of total revenue for the Company. To date the aggregate of all units presently deployed, at purchase order stage and client verbal commitment stage equal more than $2,400,000 worth of total potential revenue. RAD expects to reach $100,000 of monthly recurring revenue by this fiscal year end February 28, 2019, which represents approximately $5,000,000 of total potential revenue. RAD already has total deployments, purchase orders and verbal commitments for half of this amount to date.

On 18 September, Dentons hosted an Energy Institute event in our London office with the title "The Clash of Digitalisations". Speakers from Upside Energy, Powervault and Mixergy spoke about the Pete Project, an initiative funded by Innovate UK, that is exploring the potential of domestic hot water tanks and batteries to provide flexibility services to National Grid. Fascinating as the technological and energy-regulatory aspects of this kind of household demand-side response aggregation services are, a key common theme of the evening was the central role played in them by the analysis of large amounts of "personal data", and whether recent changes in privacy legislation help or hinder the development of such services. We produced this short article to put that discussion in context. The General Data Protection Regulation (GDPR) came into force across the European Union (EU) on 25 May 2018 and is intended to overhaul the way that companies collect and use personal data.

CEO, Martin Spencer, addresses their 2018 progress in multiple markets. For over twenty years, GeckoSystems has dedicated itself to development of "AI Mobile Robot Solutions for Safety, Security and Service(tm)." We have further cost reduced the direct manufacturing costs of our proprietary, breakthrough SafePath! It is our AI enabled human quick sense and avoid of moving and/or unmapped obstacles that opens up the immense HME/DME rehab and power wheelchair markets to GeckoSystems for a first mover opportunity. We now believe that our collision free benefit can be added to most power wheelchairs for less than $2,000 MSRP, installed. "Recently, I had the opportunity to do some Delphi Market Research with one of Pride Mobility's largest US dealers and their master rehab power wheelchair technician.