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. There are almost 350 million people worldwide with blindness or some other form of visual impairment who need to use the internet and mobile apps just like anyone else. Yet, they can only do so if websites and mobile apps are built with accessibility in mind -- and not as an afterthought. Consider these two sample buttons that you might find on a web page or mobile app. Each has a simple background, so they seem similar.

AI is evolving in all industries, but it is still difficult to determine what it will do in the future. There are so many possibilities with artificial intelligence, and it is only a matter of time before we see AI go mainstream. There are so many people who have predicted that AI will take over the world by 2050. Artificial Intelligence (AI) is the most trending topic in the global business world. AI-powered software is being developed to automate a number of tasks for businesses.

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The programme, developed by a company called SightBit, uses information collected from surveillance cameras to determine who is in the water -- an adult or child, for example -- if they are moving or limp, and the current's movement at that location. If a threat is determined, the programme sends an alert to a tablet held by the user -- a lifeguard, in this case -- with urgent instructions to act. SightBit's chief executive Netanel Eliav told AFP that he developed the technology after identifying a shortfall in how closed-circuit footage was being applied to boost safety in the water. The programme has been in use for more than a year in Ashdod, a city on Israel's Mediterranean coast that chose to deploy SightBit technology in an area at a distance from the nearest lifeguard. "We chose to locate the technology in areas away from the lifeguard towers, so the additional'eyes' there help the lifeguards very much," said Arie Turjeman, director of Ashdod's coast division.

Hepatocellular carcinoma (HCC) currently represents the fifth most common malignancy and the third-leading cause of cancer-related death worldwide, with incidence and mortality rates that are increasing. Recently, artificial intelligence (AI) has emerged as a unique opportunity to improve the full spectrum of HCC clinical care, by improving HCC risk prediction, diagnosis, and prognostication. AI approaches include computational search algorithms, machine learning (ML) and deep learning (DL) models. ML consists of a computer running repeated iterations of models, in order to progressively improve performance of a specific task, such as classifying an outcome. DL models are a subtype of ML, based on neural network structures that are inspired by the neuroanatomy of the human brain.

I have recently started exploring Neural networks, and I came across the term activation function and biases. Activation function kinda made some sense to me, but I found it difficult to get the exact essence of biases in Neural Network. Bias in Neural Networks can be thought of as analogous to the role of an intercept in linear regression. But what the heck does this mean? I very well understand that intercept is the point where the line crosses the y-axis.

Artificial intelligence (AI) technology is playing a vital role in transforming not only businesses, but entire industries, and even our day-to-day lives. Gartner forecasts that worldwide AI software revenue is set to reach $62.5 billion this year, a fairly significant increase of 21.3% from 2021. However, the research company also states that, while enterprises continue to show strong interest in AI, the reality is that deployment is lagging behind, and it will take up to 2025 for half of organisations worldwide to reach the maturity model level Gartner describes as the'stabilisation stage'. A reluctance to embrace AI and also a lack of trust, among others. "Successful AI business outcomes will depend on the careful selection of use cases," said Alys Woodward, Senior Research Director at Gartner.

Earlier this month, the EcoMotion 2022 conference took place, where companies and experts from across the automotive technology industry gathered to showcase the latest innovations defining the sector. Autonomous vehicles were also present at the conference, with new technologies showcased by companies such as the driving system verification platform Foretellix. The company's platform is used by companies like Volvo, MobilEye and Amazon Web Services to verify the safety and viability of the software used to direct Autonomous Vehicles and Advanced Driver-Assistance Systems. The company recently closed a $32m investment round, with its overall capital raised reaching $50m since it was established in 2018. The Renault-Nissan-Mitsubishi Innovation Lab in Tel Aviv was present at the conference, looking for the latest innovations to utilize in future cars and services offered by the alliance members' companies. The lab's mission statement is to advance state-of-the-art mobility, with the main focus on vision sensors, cybersecurity, EV and data & AI.

Well, it's hard not to like Brent Spiner, the nice Jewish boy from Houston who grew up to write a funny, self-mocking semi-fictional autobiography as well as star in a hit TV series. He calls his book, Fan Fiction, a "mem-noir" where an actor, conveniently named Brent Spiner, on the third season of a modest hit conveniently called "ST:TNG" is being stalked by a someone purported to be Lal, Data's short-lived robot daughter. The hapless actor finds it is as if he is living in a Raymond Chandler novel. Brent reflects on his life and how he got to this point in his career as he tries to go about shooting episodes, going to parties at the Roddenberrys, signing autographs at cons, and hanging out with Patrick Stewart, Levar Burton, and Jonathan Frakes. Yet Spiner comes across as a regular guy, grounded and grateful- and amused- at "making it" in Hollywood.

This Interesting Engineering piece highlights how even an AI built to find'helpful drugs', when tweaked just a little, can find things that are rather less helpful. Collaborations Pharmaceuticals carried out a simple experiment to see what would happen if the AI they had built was slightly altered to look for chemical weapons, rather than medical treatments. According to a paper they published in Nature Machine Intelligence journal, the answer was not particularly reassuring. When reprogrammed to find chemical weapons, the machine learning algorithm found 40,000 possible options in just six hours. These researchers had'spent decades using computers and A.I. to improve human health', yet they admitted, after the experiment, that they had been'naive in thinking about the potential misuse of trade'.