The two chip companies have signed a term sheet, according to sources with direct knowledge of the agreement. Intel has signed a term sheet to acquire the AI chip startup SambaNova Systems, two sources with direct knowledge of the agreement tell WIRED. The details of the term sheet are unknown. The agreement is non-binding, meaning the deal is not yet finalized and could be dissolved without penalty. It could take weeks or even months before regulatory approval, liability scrutiny, and financial due diligence are complete.

Healthcare analytics company MDI Health scored $20 million in Series A funding, bringing the company's total funding to $26 million. Intel Capital led the round with participation from Maverick Ventures Israel alongside existing investors Fresh.Fund, Arc Impact, Hanaco Ventures, Jumpspeed Ventures, former Optum senior vice president Richard Montwill, Welltech Ventures and Basad Ventures. Yoni Greifman, Intel Capital's investment director, will join MDI's board of directors. Israel-based MDI offers an AI-enabled tool that provides medication risk analysis based on a patient's medical records with the aim of preventing adverse drug reactions. The funds will help the company scale its U.S. and Israeli research and development teams.

The use of data within companies continues to grow exponentially. This comes at a time when data platforms and tools for analytics, data science, and AI continue to get simpler. As a result the number of data users and data applications are growing within organizations. This growth in data usage comes at a time of heightened concern for data security and privacy. On the cybersecurity front, data breaches are at an alltime high.

Chip design is a long slog of trial and error, taking years to bring a design to market. Motivo, a five year old startup from a chip industry veteran is creating software to speed up chip design from years to months using AI. Today the company announced a $12 million Series A. Intel Capital led the round along with new investors Storm Ventures and Seraph Group, as well as participation from Inventus Capital. The company reports it has now raised a total of $20 million with its previous seed funding. Motivo co-founder and CEO Bharath Rangarajan has worked in the chip industry for 30 years, and he saw a few fundamental trends and issues.

Jennifer Flynn had a problem. Shortly after joining LeadCrunch as a senior data scientist, she wanted to push out one small update of the company's software, which uses machine learning to find sales leads for its business customers. The data science team consisted of just five engineers, including her. That simple update took days and required help from the company's product development team, too. "It wasn't tenable," Flynn said, now LeadCrunch's principal data scientist.

Opaque, a new startup born out of Berkely's RISELabs, announced a $9.5 million seed round today to build a solution to access and work with sensitive data in the cloud in a secure way, even with multiple organizations involved. Intel Capital led today's investment with participation by Race Capital, The House Fund and FactoryHQ. The company helps customers work with secure data in the cloud while making sure the data they are working on is not being exposed to cloud providers, other research participants or anyone else, says company president Raluca Ada Popa. "What we do is we use this very exciting hardware mechanism called Enclave, which [operates] deep down in the processor -- it's a physical black box -- and only gets decrypted there. Company co-founder Ion Stoica, who was a co-founder at Databricks, says the startup's solution helps resolve two conflicting trends. On one hand, businesses increasingly want to make use of data, but at the same time are seeing a growing trend toward privacy. Opaque is designed to resolve this by giving customers access to their data in a safe and fully encrypted way. Data is the world's most valuable (and vulnerable) resource The company describes the solution as "a novel combination of two key technologies layered on top of state-of-the-art cloud security--secure hardware enclaves and cryptographic fortification." This enables customers to work with data -- for example to build machine learning models -- without exposing the data to others, yet while generating meaningful results. Popa says this could be helpful for hospitals working together on cancer research, who want to find better treatment options without exposing a given hospital's patient data to other hospitals, or banks looking for money laundering without exposing customer data to other banks, as a couple of examples. Investors were likely attracted to the pedigree of Popa, a computer security and applied crypto professor at UC Berkeley and Stoica, who is also a Berkeley professor and co-founded Databricks. Both helped found RISELabs at Berkeley where they developed the solution and spun it out as a company. Mark Rostick, vice president and senior managing director at lead investor Intel Capital says his firm has been working with the founders since the startup's earliest days, recognizing the potential of this solution to help companies find complex solutions even when there are multiple organizations involved sharing sensitive data. "Enterprises struggle to find value in data across silos due to confidentiality and other concerns.

Centrical, a startup developing an employee engagement and performance management platform, today announced that it raised $32 million in funding led by Intel Capital. CEO Gal Rimon says that the funds, which bring Centrical's total raised to date to $64 million, will be put toward product R&D as Centrical looks to acquire new customers. During the pandemic, as shelter-in-place orders and office closures force employees to work from home, companies are increasingly experimenting with or adopting work quality monitoring products. According to a June study by Gartner, 26% of HR leaders report having used some form of software or technology to track remote workers since the start of the health crisis. It's an uptick driven in part by concerns over performance dips that could arise from work-from-home setups.

Venture Capital firms accelerate Research work in AI labs. Every start-up or research organization requires investment to proceed with the work that they aim to do, and this requires funding from an external source that baits into the funding process. These funding organizations are called venture capitals firms and organizations. Over the years, the venture capitalist firm has pro-actively invested in technology. Artificial Intelligence and its subsidiaries, and big data are counted as the top investments by venture capitalist firms.

Manasi Vartak, founder and CEO of Verta, conceived of the idea of the open-source project ModelDB database as a way to track versions of machine models while she was still in grad school at MIT. After she graduated, she decided to expand on that vision to build a product that could not only track model versions, but provide a way to operationalize them -- and Verta was born. Today, that company emerged from stealth with a $10 million Series A led by Intel Capital with participation from General Catalyst, which also led the company's $1.7 million seed round. Beyond providing a place to track model versioning, which ModelDB gave users, Vartak wanted to build a platform for data scientists to deploy those models into production, which has been difficult to do for many companies. She also wanted to make sure that once in production, they were still accurately reflecting the current data and not working with yesterday's playbook.

As companies increase their investments in artificial intelligence (AI), there is growing pressure on developers and engineers to deploy AI projects more quickly and at greater scale across the enterprise. Simply evaluating the ever-expanding universe of AI tools and services-- often designed for different users and purposes--is a significant challenge in this growing and fast-moving environment. To address this challenge, we have created the AI Infrastructure Stack, a landscape map that brings greater clarity to the AI ecosystem by charting the layers of the AI technical stack and the vendors within each layer. At Intel Capital, this helps us identify the investments we believe will have the greatest positive impact on the future of AI, but it also helps developers and engineers identify the resources they need to deliver their AI projects in the most efficient and effective way possible. This technical infrastructure stack is focused on horizontal solutions that address fundamental needs in developing AI, regardless of the type of company or industry where it's being deployed.