While immunotherapies have revolutionized cancer treatment, they are currently effective only for a small subset (from 20% to 30%) of patients. Tel-Aviv-based Nucleai is developing AI software for image analysis and modeling of pathology data to assist in the development of more effective drugs. The long-term goal of the 3-year-old startup is to be "a leader in precision medicine," says its co-founder and CEO, Avi Veidman. Nucleai's team has more than 50 years of cumulative AI experience gained in the Israeli Intelligence Corps--including satellite image analysis--plus the expertise of physicians and healthcare professionals, resulting in a multi-disciplinary approach to the challenge of ineffective predictive biomarkers. To find a better answer, "we combine different sources of information, just like what we did in intelligence," says Veidman. "The cancer does not care about your specialty," he observes.
AI21 Labs, a startup formed by veterans from an elite tech unit in the IDF to build AI systems, announced on Thursday it raised $34.5 million in total equity capital to work on its AI-based writing solutions and offerings. The funding includes a seed round of $9.5 million in January 2019 and the latest round of $25 million led by Pitango First, the seed and early-stage fund of Pitango's investment platform. Pitango is Israel's largest venture capital fund and was co-founded by Chemi Peres, the son of former president Shimon Peres. The VC focuses on core technologies like deep tech, AI, and machine learning. Other investors in the latest funding round included TPY Capital, another VC headquartered in Tel Aviv.
Recently, a team of researchers from Facebook AI and Tel Aviv University proposed an AI system that solves the multiple-choice intelligence test, Raven's Progressive Matrices. The proposed AI system is a neural network model that combines multiple advances in generative models, including employing multiple pathways through the same network. Raven's Progressive Matrices, also known as Raven's Matrices, are multiple-choice intelligence tests. The test is used to measure abstract reasoning and is regarded as a non-verbal estimate of fluid intelligence. In this test, a person tries to finish the missing location in a 3X3 grid of abstract images.
Multiple choice tests provide test-takers the ability to compare answers to eliminate choices (or guess the correct one). Each choice can be compared with the question to infer patterns that might have been missed; it's arguably the ability to narrow down the right answer from sets of answers that's the test of true comprehension. Inspired by this, researchers at Tel Aviv University and Facebook developed a machine learning model that generates answers to the Raven Progressive Matrix (RPM), a type of intelligence test where the goal is to complete the location in a grid of abstract images. The coauthors claim that their algorithm is not only able to generate a plausible set of answers competitive with state-of-the-art methods, but that it could be used to build an automatic tutoring system that adjusts to the proficiencies of individual students. RPM is a nonverbal test typically used in educational settings like schools.
Deep learning startup Deci today announced that it raised $9.1 million in a seed funding round led by Israel-based Emerge. According to a spokesperson, the company plans to devote the proceeds to customer acquisition efforts as it expands its Tel Aviv workforce. Machine learning deployments have historically been constrained by the size and speed of algorithms and the need for costly hardware. In fact, a report from MIT found that machine learning might be approaching computational limits. A separate Synced study estimated that the University of Washington's Grover fake news detection model cost $25,000 to train in about two weeks.
A new paper published by researchers affiliated with Facebook and Tel-Aviv University investigates whether machine learning language models can understand basic sets of instructions. The researchers propose a test dubbed the Turking Test to examine a model's ability to follow natural language instructions. Despite what the researchers characterize as a lenient evaluation methodology, they observed that a pretrained language model performed poorly across all tasks. One of the fundamental problems in AI is building a model that can generalize to previously unseen tasks. Recent work proposes a few-shot inference approach, in which a language model is conditioned on a few examples of a new task, followed by input for the model to process.
In a move to expand its business into the logistics and delivery segment, ride-hailing startup Via today announced that it acquired Fleetonomy for an undisclosed sum. Via, which says it plans to apply Fleetonomy's expertise in demand prediction and fleet utilization to support fully integrated, digitally powered logistics solutions, says the pandemic has highlighted the growing need for essential services and goods delivery. Tel Aviv-based Fleetonomy, which was founded in 2017 by CEO Israel Duanis and CTO Lior Gerenstein, taps AI to analyze data and deliver insights with the goal of maximizing inventory and promoting proactive maintenance. The company provides white label ride-sharing and on-demand car subscription services that can accommodate semiautonomous and autonomous fleets. With Fleetonomy's cloud-based suite of tools, managers can simulate services before deploying cars on the road, adjusting for factors such as fleet size, parking, charging locations, demand, and more.
Hailo, a Tel Aviv-based startup best known for its high-performance AI chips, today announced the launch of its M.2 and Mini PCIe high-AI acceleration modules. Based around its Hailo-8 chip, these new models are meant to be used in edge devices for anything from smart city and smart home solutions to industrial applications. Today's announcement comes about half a year after the company announced a $60 million Series B funding round. At the time, Hailo said it was raising those new funds to roll out its new AI chips, and with today's announcement, it's making good on this promise. In total, the company has now raised $88 million.
Imagine if voice technology could be used to diagnose diseases! This could be a reality if voice tech is used to identify non-speech sounds, such as coughs. This focus is of particular interest at the moment as the world's governments rally resources to protect populations against COVID-19. This is one area of focus for this week's guest, Prof. Ami Moyal, President, Afeka Tel Aviv College of Engineering, Israel. Prof. Ami also talks about the future of voice technology and what we should be teaching children for them to be successful in the world.
Old-fashioned police forensics analysis met hi-tech computer algorithms in a new study of 2,500-year-old pottery sherds, in which Tel Aviv University researchers conclude that literacy was widespread enough for the fledgling People of the Book to have penned parts of the Bible in the 7th century BCE. "The high literacy rate detected within the small Arad stronghold… demonstrates widespread literacy in the late 7th century BCE Judahite military and administration apparatuses, with the ability to compose biblical texts during this period a possible by-product," write the researchers. This is the first study to combine forces between AI algorithms and human forensics know-how, the researchers note. The study, "Forensic document examination and algorithmic handwriting analysis of Judahite biblical period inscriptions reveal significant literacy level," was published September 9 in the prestigious online PLOS journal. Get The Times of Israel's Daily Edition by email and never miss our top stories Free Sign Up The study combines high-resolution imaging methods and complex computer algorithms with trusted police handwriting analysis to prove that the examined 18 texts had no fewer than 12 different authors way back in circa 600 BCE.