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The big new idea for making self-driving cars that can go anywhere

MIT Technology Review

Investors have sunk more than $100 billion into building cars that can drive by themselves. That's a third of what NASA spent getting humans to the moon. Yet despite a decade and a half of development and untold miles of road testing, driverless tech is stuck in the pilot phase. "We are seeing extraordinary amounts of spending to get very limited results," says Kendall. That's why Wayve and other autonomous-vehicle startups like Waabi and Ghost, both in the US, and Autobrains, based in Israel, are going all in on AI. Branding themselves AV2.0, they're betting that smarter, cheaper tech will let them overtake current market leaders.

How an AI robot can help seniors battle loneliness - MedCity News


Powered by AI, ElliQ is a voice-operated robotic care companion designed to foster independence and provide support for older adults. About 1 in 4 adults 65 and older are considered to be socially isolated, putting them at increased risk for a wide range of health conditions, from dementia to heart disease and stroke. Many don't have family and friends who live nearby or visit regularly; and the number of professional caregivers is failing to keep up with demand as the U.S. population ages. Responding to the need, the New York State Office for the Aging announced Wednesday that it is partnering with Intuition Robotics to bring an AI robotic care companion into the homes of 800 older adults as part of the state's efforts to battle social isolation and support aging in place. NYSOFA is working with local offices for the aging and other partners to identify older adults who would most benefit from ElliQ by Intuition Robotics, which the Israeli company describes as first-ever proactive and empathetic AI robotic care companion.

Top 5 smart personal home robots you can buy in 2022


Robots are not limited to industrial works anymore! Thanks to the integration of artificial intelligence and voice recognition, robots are slowly invading our smart homes embedded with devices like wireless security cameras, Smart TVs, Amazon's Alexa, Amazon Echo, Google Assistant, Philips Hue lightbulbs, Ecobee4, etc. And it is not a secret that machine learning software development is on rise now. A lot of clients are coming to develop personalized ML solutions for their businesses. ABI Research predicts that this integration will grow, and by 2024 that over 79 million homes in the world will have a robot in the house.

An AI-Based Approach to Monitor, Expose, and Counter Anti-Hindu Hate


MyIndMakers enables the exchange of Global Ideas and Solutions from India. All day news updates related to Business, Hindu, Hinduism, India, Indic, Culture, Travel, Religion, Politics, Foreign Policy, Modi, Swami, BJP, Congress, Trump, Biden, Israel, Jihad, Christianity, China, Japan, Book Reviews, Movie Reviews, Indian Artciles, Blogs, Interviews, Podcasts, Videos, MyIndBook, MyIndMakers,,Hindumisia,, AI-based approach, Deep Learning, Anti-Defamation League, Online Hate Index

A Deeper Understanding of Deep Learning

Communications of the ACM

Deep learning should not work as well as it seems to: according to traditional statistics and machine learning, any analysis that has too many adjustable parameters will overfit noisy training data, and then fail when faced with novel test data. In clear violation of this principle, modern neural networks often use vastly more parameters than data points, but they nonetheless generalize to new data quite well. The shaky theoretical basis for generalization has been noted for many years. One proposal was that neural networks implicitly perform some sort of regularization--a statistical tool that penalizes the use of extra parameters. Yet efforts to formally characterize such an "implicit bias" toward smoother solutions have failed, said Roi Livni, an advanced lecturer in the department of electrical engineering of Israel's Tel Aviv University.

Israeli firm hopes AI can curb drownings


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.

Here's how AI, computer vision will change driving - EcoMotion 2022


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.

$35 Million In New Funding For AI To Personalize Cancer Treatment


Israeli startup OncoHost announced today an upsized and oversubscribed $35 million Series C funding round, led by ALIVE Israel HealthTech VC, with the participation of Leumi Partners, Menora Mivtachim, OurCrowd and other existing investors. Clinical trial results have shown OncoHost's AI-powered precision oncology platform to have remarkably high accuracy in assessing non-small cell lung cancer (NSCLC) patient response at three months, six months and one year. Through one blood test pre-treatment, the company's multi-patented platform also provides clinicians with potential combination strategies to overcome treatment resistance. Last year, OncoHost CEO Dr. Ofer Sharon told me that "For immunotherapy, the most important treatment modality we have today, the response rate on average across all cancer types is about 20%. With all the promise of immunotherapy, if you have ten patients waiting in your waiting room with advanced cancer, only two will be alive in two years."

Business intelligence firm Pyramid Analytics raises $120M – TechCrunch


Business intelligence is an increasingly well-funded category in the software-as-a-service market. By handling large amounts of data to analyze and benchmark lines of business, BI promises to help identify, develop and otherwise create new revenue opportunities. Pervasive BI remains elusive, but statistics on the category reveal that about a third of employees use BI tools for analytics to inform strategy. The big data and business analytics market could be worth $684 billion by 2030, according to Valuates Reports, if such outrageously high estimates are to be believed. The segment contains too many vendors to count -- a few include Noogata, Fractal Analytics, Tredence, LatentView and Mu Sigma.

A Product Manager's 600-Word Guide to Machine Learning


Machine learning (ML) is a technology or field of computer science that learns from historical data to make accurate predictions or decisions. This could be looking at the purchasing patterns of a buyer and recommending products to a similar buyer. Or, this could be analyzing weather data to predict what the weather would be like on a particular day. There is no magic here. To make things easier, imagine you're at a coffee shop with your closest friend. The barista asks your friend what kind of coffee they want.