Thinking Machines Lab, led by a group of prominent former OpenAI researchers, is betting that fine-tuning cutting-edge models will be the next frontier in AI. Thinking Machines Lab, a heavily funded startup cofounded by prominent researchers from OpenAI, has revealed its first product--a tool called Tinker that automates the creation of custom frontier AI models. "We believe [Tinker] will help empower researchers and developers to experiment with models and will make frontier capabilities much more accessible to all people," said Mira Murati, cofounder and CEO of Thinking Machines, in an interview with WIRED ahead of the announcement. Big companies and academic labs already fine-tune open source AI models to create new variants that are optimized for specific tasks, like solving math problems, drafting legal agreements, or answering medical questions. Typically, this work involves acquiring and managing clusters of GPUs and using various software tools to ensure that large-scale training runs are stable and efficient.

Meta AI, the most interesting thing you can do with Ray-Ban Meta glasses, will soon be available to more people. The company's Live Translation feature is rolling out to all the product's markets, and Live AI (where you can hold a free-flowing conversation about what you're looking at) will soon be available in the US and Canada. In addition, glasses owners in the EU can finally use Meta AI with their high-tech specs. Live translation, previously available in early access, is now rolling out in every region where Ray-Ban Meta glasses are available. Handy for trips abroad or chats with locals who speak a different language, the AI-powered feature speaks a translation in your preferred language in real time.

This paper introduces a new IncidentAI dataset for safety prevention. Different from prior corpora that usually contain a single task, our dataset comprises three tasks: named entity recognition, cause-effect extraction, and information retrieval. The dataset is annotated by domain experts who have at least six years of practical experience as high-pressure gas conservation managers. We validate the contribution of the dataset in the scenario of safety prevention. Preliminary results on the three tasks show that NLP techniques are beneficial for analyzing incident reports to prevent future failures. The dataset facilitates future research in NLP and incident management communities. The access to the dataset is also provided (the IncidentAI dataset is available at: https://github.com/Cinnamon/incident-ai-dataset).

Summary: The Transcarent Analytics and Reporting team empowers the company to make data-driven decisions and provides critical business insights that help us execute in a world-class fashion. We are seeking a talented and motivated technical expert to accelerate our efforts to drive trust, adoption, and democratization of insights externally to our clients and members as well as internally to our stakeholders and leaders. The Analytics Data Engineer will work closely with our Data Engineering, Product, and Solution stakeholders to deliver well-defined, transformed, tested, documented, and code-reviewed analytical datasets that would be single source of truth for reliable, and consistent results. The ideal candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, and applying analytical rigor to inform business decisions. They will work very efficiently to deliver the right solutions and continuously think of how to best automate and expand the delivery of the analytical solutions.

As its stock hit a record high Friday, Microsoft's (MSFT) price target was raised on the view that its products and initiatives around artificial intelligence are undervalued. X KeyBanc Capital Markets analyst Brent Bracelin raised his price target on Microsoft to 106 from 94 and maintained a rating of overweight. "After meeting with senior leaders at Microsoft who are spearheading new AI products and initiatives, we came away impressed with Microsoft's AI product scope, ambitions to differentiate, and the three-year potential to capitalize on this wide-open market opportunity," Bracelin wrote in a research note to clients. Microsoft shares climbed 1.7% to close at 89.60 on the stock market today, setting a new closing high. Bracelin said he met with senior leaders at Microsoft last month and came away "very impressed by Microsoft's AI platform and the traction with embedding and implementing AI services in the enterprise."

There will be many people who will say it does exist and has working technologies, hardware and software. It is an interesting error in thinking to focus on closed system devices/products as to what Ubiquity (IoT3) is. Devices are used to get across the point of various types of connections and networks being accessed. But more importantly in a full implementation of the concept of Ubiquity (often described as the IoT) devices may not even be owned anymore. The ownership of devices ceases to be important if you can own your digital identity, can verify it and establish your own ecosystem of assets in Blockchain.

European software major SAP and startup accelerator Techstars will invest in at least 10 artificial intelligence (AI) startups every year through its SAP.iO Foundry in Berlin. SAP.iO is an initiative of the tech giant to create an ecosystem of products and software by working with entrepreneurs. In 2017, five Indian startups were among 10 companies selected by SAP.iO's AI accelerator's first batch. "We are looking at enterprise applications from startups that are founded around a year ago," Alexa Gorman, global vice-president of SAP.iO Fund, told VCCircle over a telephone call from Berlin. "By restricting our focus, we can add value in terms of marketing assistance and mentorship for these startups."

Almost a quarter century ago, a book was written about how organizations would focus on share of customer as opposed to share of market, building a personalized collaboration driven by big data. With advanced analytics, banking may finally getting close to realizing this vision. In 1993, a then revolutionary book, "The One to One Future: Building Relationships One Customer at a Time" was published, proposing the idea that as technology makes it affordable to track individual customers, marketing shifts from finding customers for products to finding products for customers. According to the authors, Don Peppers and Martha Rogers, Ph.D., a company could use technology to gather information about, and to communicate directly with, individuals to form a commercial bond. The book became a bestseller, and was on every marketer's bookshelf … almost a quarter century ago.

As its stock hit a record high Friday, Microsoft's (MSFT) price target was raised on the view that its products and initiatives around artificial intelligence are undervalued. X KeyBanc Capital Markets analyst Brent Bracelin raised his price target on Microsoft to 106 from 94 and maintained a rating of overweight. "After meeting with senior leaders at Microsoft who are spearheading new AI products and initiatives, we came away impressed with Microsoft's AI product scope, ambitions to differentiate, and the three-year potential to capitalize on this wide-open market opportunity." Bracelin wrote in a research note to clients. Microsoft shares were up 0.9%, near 88.90 during morning trading in the stock market today, setting a new high.

The quest to give machines human-level intelligence has been around for decades, and it has captured imaginations for far longer -- think of Mary Shelley's Frankenstein in the 19th century. Artificial intelligence, or AI, was born in the 1950s, with boom cycles leading to busts as scientists failed time and again to make machines act and think like the human brain. But this time could be different because of a major breakthrough -- deep learning, where data structures are set up like the brain's neural network to let computers learn on their own. Together with advances in computing power and scale, AI is making big strides today like never before. Frank Chen, a partner specializing in AI at top venture capital firm Andreessen Horowitz, makes a case that AI could be entering a golden age.