Alibaba is making AI news again, releasing another Qwen reasoning model, QwQ-32B, which was trained and scaled using reinforcement learning (RL). The Qwen team says it “has the potential to enhance model performance beyond conventional pretraining and post-training methods.” QwQ-32B, a 32 billion parameter model, “achieves performance comparable to DeepSeek-R1, which boasts 671 billion parameters (with 37 billion activated),” Alibaba claims. While parameters refer to the total set of adjustable weights and biases in the model’s neural network, “activated” parameters are a subset used for a specific inference task, like generating a response. Continue reading Alibaba Says Qwen Reasoning Model on Par with DeepSeek

Alibaba has open-sourced its Wan 2.1 video- and image-generating AI models, heating up an already competitive space. The Wan 2.1 family, which has four models, is said to produce “highly realistic” images and videos from text and images. The company has since December been previewing a new reasoning model, QwQ-Max, indicating it will be open-sourced when fully released. The move comes after another Chinese AI company, DeepSeek, released its R1 reasoning model for free download and use, triggering demand for more open-source artificial intelligence. Continue reading Highly Realistic Alibaba GenVid Models Are Available for Free

Barely two weeks after the launch of its OmniHuman-1 AI model, ByteDance has released Goku, a new artificial intelligence designed to create photorealistic video featuring humanoid actors. Goku uses text prompts to create among other things, realistic product videos without the need for human actors. This last is a boon for ByteDance social media unit TikTok. Goku is open source, trained on a large dataset of roughly 36 million video-text pairs and 160 million image-text pairs. Goku’s debut is received as more bad news for OpenAI in the form of added competition, but a positive step for global enterprise. Continue reading ByteDance’s Goku Video Model Is Latest in Chinese AI Streak

Model training continues to hit new lows in terms of cost, a phenomenon known as the commoditization of AI that has rocked Wall Street. An AI reasoning model created for under $50 in cloud compute credits is reportedly performing comparably to established reasoning models such as OpenAI o1 and DeepSeek-R1 on tests of math and coding aptitude. Called s1-32B, it was created by researchers at Stanford and the University of Washington by customizing Alibaba’s Qwen2.5-32B-Instruct, feeding it 1,000 prompts with responses sourced from Google’s new Gemini 2.0 Flash Thinking Experimental reasoning model. Continue reading Reasoning Model Competes with Advanced AI at a Lower Cost

Jack Dorsey’s financial tech and media firm Block (formerly Square) has released a platform for building AI agents: Codename Goose. Previously available in beta, Goose is primarily designed to build agents for coding and software development, but Block built in many basic features that could be applied to general purpose pursuits. Because it is open source and offered under Apache License 2.0, the hope is that developers will apply it to varied use cases. A leading feature of Codename Goose is its flexibility. It can integrate a wide range of large language models, letting developers use it with their preferred model. Continue reading Codename Goose: Block Unveils Open-Source AI Agent Builder

Meta Platforms has packed more artificial intelligence into a smaller package with Llama 3.3, which the company released last week. The open-source large language model (LLM) “improves core performance at a significantly lower cost, making it even more accessible to the entire open-source community,” Meta VP of Generative AI Ahmad Al-Dahle wrote on X social. The 70 billion parameter text-only Llama 3.3 is said to perform on par with the 405 billion parameter model that was part of Meta’s Llama 3.1 release in July, with less computing power required, significantly lowering its operational costs. Continue reading Meta’s Llama 3.3 Delivers More Processing for Less Compute

Lightricks has released an AI model called LTX Video (LTXV) it says generates five seconds of 768 x 512 resolution video (121 frames) in just four seconds, outputting in less time than it takes to watch. The model can run on consumer-grade hardware and is open source, positioning Lightricks as a mass market challenger to firms like Adobe, OpenAI, Google and their proprietary systems. “It’s time for an open-sourced video model that the global academic and developer community can build on and help shape the future of AI video,” Lightricks co-founder and CEO Zeev Farbman said. Continue reading Lightricks LTX Video Model Impresses with Speed and Motion

Anthropic is releasing what it hopes will be a new standard in data integration for AI. Called the Model Context Protocol (MCP), its goal is to eliminate the need to customize each integration by having code written each time a company’s data is connected to a model. The open-source MCP tool could become a universal way to link data sources to AI. The aim is to have models querying databases directly. MCP is “a new standard for connecting AI assistants to the systems where data lives, including content repositories, business tools, and development environments,” according to Anthropic. Continue reading Anthropic Protocol Intends to Standardize AI Data Integration

The GitHub Secure Open Source Fund will award financing to select applicants in a program designed to fuel security and sustainability for open-source projects. Applications are open now and close on January 7. During that time, 125 projects will be selected for a piece of the $1.25 million investment fund, made possible through the participation of American Express, the Alfred P. Sloan Foundation, Chainguard, HeroDevs, Kraken, Mayfield Fund, Microsoft, Shopify, Stripe and others. In addition to monetary support, recipients will be invited to take part in a three-week educational program. Continue reading GitHub Promotes Open-Source Security with Funding Initiative

Microsoft is previewing GitHub Copilot for Azure in an ambitious expansion of its AI app development toolkit that some say could fundamentally change how developers build software for the AI era. The new premise is that switching from one software to another, as developers often do, should be seamless, not disruptive — sort of a real-time language translation and integration system for code. To fend off the move by Microsoft, AWS announced it is making its Q Developer AI code assistant available as an inline chat add-on accessible from IDEs like JetBrains and Microsoft’s own Visual Studio. Continue reading Microsoft, Amazon Jockey for Lead Among AI Code Assistants

OpenAI has announced Swarm, an experimental framework that coordinates networks of AI agents, and true to its name the news has kicked over a hornet’s nest of contentious debate about the ethics of artificial intelligence and the future of enterprise automation. OpenAI emphasizes that Swarm is not an official product and says though it has shared the code publicly it has no intention of maintaining it. “Think of it more like a cookbook,” OpenAI engineer Shyamal Anadkat said in a social media post, calling it “code for building simple agents.” Continue reading OpenAI Tests Open-Source Framework for Autonomous Agents

Microsoft has released a suite of “Trustworthy AI” features that address concerns about AI security and reliability. The four new capabilities include Correction, a content detection upgrade in Microsoft Azure that “helps fix hallucination issues in real time before users see them.” Embedded Content Safety allows customers to embed Azure AI Content Safety on devices where cloud connectivity is intermittent or unavailable, while two new filters flag AI output of protected material. Additionally, a transparency safeguard providing the company’s AI assistant, Microsoft 365 Copilot, with specific “web search query citations” is coming soon. Continue reading New Microsoft Safety Tools Fix AI Flubs, Detect Proprietary IP

Alibaba Cloud last week globally released more than 100 new open-source variants of its large language foundation model, Qwen 2.5, to the global open-source community. The company has also revamped its proprietary offering as a full-stack AI-computing infrastructure across cloud products, networking and data center architecture, all aimed at supporting the growing demands of AI computing. Alibaba Cloud’s significant contribution was revealed at the Apsara Conference, the annual flagship event held by the cloud division of China’s e-retail giant, often referred to as the Chinese Amazon. Continue reading Alibaba Cloud Ups Its AI Game with 100 Open-Source Models

Amazon is transferring its OpenSearch platform to the Linux Foundation’s new OpenSearch Software Foundation. By handing a third-party the open-source project it has developed internally since 2021, Amazon hopes to accelerate collaboration in data-driven search and analytics, an area of focus due to the proliferation of model training. Not to be confused with commercial search (Google, Bing), engines like OpenSearch are geared toward enterprise and academia. Because it is licensed under Apache 2.0, OpenSearch is a viable starting point for organizations that customize internal platforms for searching, monitoring and analyzing large volumes of data. Continue reading AWS Transfers OpenSearch Stewardship to Linux Foundation

In its ongoing effort to strike the right balance between ad targeting and consumer data collection, Google Ads is introducing a new process it calls “confidential matching.” Relying on the hardware and software used for confidential computing in Trusted Execution Environments (TEEs), Google says this new approach allows businesses to securely manage their first-party data. They’ll still be able to use it to reach customers and measure the impact of their digital ad campaigns, but the information will be isolated “during processing so that no one — including Google — can access the data being processed.” Continue reading Google Ads Adopts Open-Source TEE Setup for Data Privacy