Latest breakthroughs in large language models and generative AI shaping the future of artificial intelligence and machine learning.
SAP’s newest offering, RPT‑1, arrives with a promise that feels almost nostalgic for a time when businesses could plug a model straight into a workflow without the heavy lifting of fine‑tuning.
Zendesk is betting on a two‑pronged upgrade to its support platform, unveiling both GPT‑5 and a new monitoring layer called HyperArc.
Cognizant is putting Anthropic’s Claude into the hands of a massive workforce—350,000 employees, or roughly 3.5 lakh staff, will gain direct access to the model this month.
The Gemma series has slipped into the spotlight not because of its performance, but because of how it’s being handled.
In the rush to lean on large language models, many of us have started treating a chatbot’s output like a ready‑made email draft or a quick answer to a colleague’s query. The original title, “Your Friend Asked You a Question.
Coca‑Cola rolled out its first AI‑driven holiday spot this season, banking on the brand’s familiar red‑and‑white iconography to catch eyes during the most commercial‑heavy time of the year.
Google’s AI Studio promises a smoother hand‑off from conversation to implementation, but the real test lies in how it bridges prompt tweaking with actual code.
Why did Google yank its newest AI offering just weeks after a high‑profile senator claimed the system invented an assault story?
Meta’s latest LLM, dubbed the Free Transformer, takes a different tack on how generative models handle choice.
Why does testing matter when you’re building an LLM‑driven app? In the crowded field of generative AI, developers need a way to tell whether a model’s reply meets expectations without manually sifting through every result.
The conversation around artificial intelligence has shifted from asking whether machines can generate text to questioning how they act when given autonomy.
OpenAI has been rolling out a new class of “safeguard” models that sit alongside its flagship language engines, promising tighter alignment with policy constraints while still delivering fluent output.