Twelve Labs has raised $30 million in funding for its efforts to train video-analyzing models. The San Francisco-based company has received strategic investments from notable enterprise infrastructure providers Databricks and SK Telecom as well as Snowflake Ventures and HubSpot Ventures. Twelve Labs targets customers using video across a variety of fields including media and entertainment, professional sports leagues, content creators and business users. The funding coincides with the release of Twelve Labs’ new video foundation model, Marengo 2.7, which applies a multi-vector approach to video understanding. Continue reading Twelve Labs Creating AI That Can Search and Analyze Video

Amazon Web Services is building a supercomputer in collaboration with Anthropic, the AI startup in which the e-commerce giant has an $8 billion minority stake. Hundreds of thousands of AWS’s flagship Trainium chips will be amassed in an “Ultracluster” that when it is completed in 2025 will be one of the largest supercomputers in the world for model training, Amazon says. The company announced the general availability of AWS Trainium2-powered Amazon Elastic Compute Cloud (EC2) virtual servers as well as Trn2 UltraServers designed to train and deploy AI models and teased next-generation Trainium3 chips. Continue reading AWS Building Trainium-Powered Supercomputer with Anthropic

Databricks Apps is a new platform designed to make building internal data and AI applications something that can be done in a few clicks. Available now in public preview on AWS and Azure, the template-based system lets users weave data and frameworks of choice into full-featured apps that can run in the Databricks environment. The company says the system can code and deploy a secure data app with AI integration in five minutes. “Ideal use cases include data visualization, AI applications, self-service analytics and data quality monitoring,” according to the San Francisco-based company. Continue reading Databricks Previews Toolkit for Internal Data, AI App Creation

Meta’s Llama 3.2 release includes two new multimodal LLMs, one with 11 billion parameters and one with 90 billion — considered small- and medium-sized — and two lightweight, text-only models (1B and 3B) that fit onto edge and mobile devices. Included are pre-trained and instruction-tuned versions. In addition to text, the multimodal models can interpret images, supporting apps that require visual understanding. Meta says the models are free and open source. Alongside them, the company is releasing “the first official Llama Stack distributions,” enabling “turnkey deployment” with integrated safety. Continue reading Meta Unveils New Open-Source Multimodal Model Llama 3.2

French startup Mistral AI has released its first large language model for coding. Codestral gives developers looking for a code-native AI tool an option to Meta’s Code Llama, Microsoft’s GitHub Copilot and Amazon Q. Fluent in 80 programming languages — including Python, C++ and JavaScript — Codestral can complete code, write tests, and augment partial code “using a fill-in-the-middle mechanism,” while reducing “the risk of errors and bugs,” according to the company. The new LLM is described as open, but its license prohibits commercial use of both Codestral and its outputs. Continue reading Mistral Development Tool Knows 80 Programming Languages

Pursuant to his goal of “building the world’s leading AI,” Meta Platforms CEO Mark Zuckerberg announced Friday that Meta AI is upgrading to Llama 3 concurrent with a rollout of its open-source chatbot across the company’s social platforms, integrating it into the search boxes atop WhatsApp, Instagram, Facebook and Messenger. There is also a website, meta.ai, for those who prefer browser access. Reports of Meta upgrading its social AI capabilities began leaking out early last week, albeit on a more limited test scale than what Zuckerberg announced, which, excepting Threads, is cross-platform. Continue reading Meta AI Assistant Is Launching Across Platforms with Llama 3

Databricks, a San Francisco-based company focused on cloud data and artificial intelligence, has released a generative AI model called DBRX that it says sets new standards for performance and efficiency in the open source category. The mixture-of-experts (MoE) architecture contains 132 billion parameters and was pre-trained on 12T tokens of text and code data. Databricks says it provides the open community and enterprises who want to build their own LLMs with capabilities previously limited to closed model APIs. Compared to other open models, Databricks claims it outperforms alternatives including Llama 2-70B and Mixtral on certain benchmarks. Continue reading Databricks DBRX Model Offers High Performance at Low Cost

Based on the premise that it is impractical to deploy an all-purpose LLM for specific use cases, a group of researchers from Google, Baidu, DeepMind and Meta founded Reka AI in July 2022. A year later the company has emerged from stealth mode with news of $58 million in Series A funding led by DST Global and Radical Ventures. Strategic partner Snowflake Ventures also participated, along with angel investor Nat Friedman, former CEO of GitHub. The Sunnyvale, California-based startup says it is building “enterprise-grade state-of-the-art AI assistants for everyone, regardless of language and culture.” Continue reading Reka AI Raises $58 Million to Customize LLMs for Enterprise

Data management firm Databricks has agreed to purchase generative AI company MosaicML in a deal valued at $1.3 billion. The three-year-old generative AI startup has developed a platform it says makes it “fast, cost-effective, and easy” for companies to train LLMs and deploy tools to use them. MosaicML has privately raised roughly $64 million to date. Its last valuation was $222 million in January, which means it was purchased for a healthy 6x multiple in a move that appears to prime Databricks for what one brokerage calls an “inevitable” IPO. Continue reading Databricks Acquiring OpenAI Competitor MosaicML for $1.3B

Meta Platforms CEO Mark Zuckerberg received a letter this week from Senators Richard Blumenthal and Josh Hawley of the Subcommittee on Privacy, Technology & the Law that took the executive to task for an online leak of the company’s LLaMA artificial intelligence system. The 65-billion parameter language model, which is still under development, was open-sourced in February. Available on request through Meta’s GitHub portal, it wound up on 4chan and BitTorrent “making it available to anyone, anywhere in the world, without monitoring or oversight,” the senators wrote. Continue reading Senators Question Meta Platforms About Recent LLaMA Leak