Senior AI Reporter
Emilia David writes about AI, focusing on policy, responsible and ethical AI, and productivity platforms. She’s written about financial technology, the capital markets, consumer technology, commodities, energy, trade policies, labor, and politics. Her work has appeared on The Verge, Insider, Venture Capital Journal, WatersTechnology, American Metal Market, CNBC.com, DNAinfo, and BusinessWorld.
Managing and maintaining AI systems remains a challenge for many enterprises, particularly with the potential for agentic sprawl to expose businesses to risky entry points.
Despite new methods emerging, enterprises continue to turn to autonomous coding agents and code generation platforms. The competition to keep developers working on their platforms, coming from tech companies, has also heated up.
Understanding how models choose to respond, a big selling point of reasoning models for enterprises, can provide a level of trust for organizations when they turn to AI models for insights.
ChatGPT is about to become faster and more conversational as OpenAI upgrades its flagship model GPT-5 to GPT-5.1.
By now, enterprises understand that retrieval augmented generation (RAG) allows applications and agents to find the best, most grounded information for queries. However, typical RAG setups could be an engineering challenge and also exhibit undesirable traits.
The new features, announced today, include additional governance tools for enterprises and expanding the capabilities for creating agents with just a few lines of code, moving faster with state-of-the-art context management layers and one-click deployment, as well as managed services for scaling production and evaluation, and support for identifying agents.
SAP aims to displace more general large language models with the release of its own foundational “tabular” model, which the company claims will reduce training requirements for enterprises.
The recent controversy surrounding Google’s Gemma model has once again highlighted the dangers of using developer test models and the fleeting nature of model availability.
Enterprises, eager to ensure any AI models they use adhere to safety and safe-use policies, fine-tune LLMs so they do not respond to unwanted queries.
Enterprises looking to sell goods and services online are waiting for the backbone of agentic commerce to be hashed out; but PayPal is hoping its new features will bridge the gap.
Some enterprises are best served by fine-tuning large models to their needs, but a number of companies plan to build their own models, a project that would require access to GPUs.
China’s Ant Group, an affiliate of Alibaba, detailed technical information around its new model, Ring-1T, which the company said is “the first open-source reasoning model with one trillion total parameters.”