Destination
Out-analyzing analysts: OpenAI’s Deep Research pairs reasoning LLMs with agentic RAG to automate work — and replace jobs

OpenAI’s Deep Research pairs advanced reasoning LLMs with agentic RAG, delivering automated reports that rival human analysts — at a fraction of the cost. This breakthrough AI tool could redefine knowledge work across industries, from finance to healthcare, while raising critical questions about job displacement. Read on to explore how OpenAI is reshaping enterprise AI workflows and setting new benchmarks for research automation [...]

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venturebeat
Google’s new Deep Research and Deep Research Max agents can search the web and your private data

Google on Monday unveiled the most significant upgrade to its autonomous research agent capabilities since the product's debut, launching two new agents — Deep Research and Deep Research Max †[...]

Match Score: 271.70

venturebeat
Microsoft built Phi-4-reasoning-vision-15B to know when to think — and when thinking is a waste of time

Microsoft on Tuesday released Phi-4-reasoning-vision-15B, a compact open-weight multimodal AI model that the company says matches or exceeds the performance of systems many times its size — while co [...]

Match Score: 213.53

venturebeat
Six data shifts that will shape enterprise AI in 2026

For decades the data landscape was relatively static. Relational databases (hello, Oracle!) were the default and dominated, organizing information into familiar columns and rows.That stability eroded [...]

Match Score: 142.25

venturebeat
With 91% accuracy, open source Hindsight agentic memory provides 20/20 vision for AI agents stuck on failing RAG

It has become increasingly clear in 2025 that retrieval augmented generation (RAG) isn't enough to meet the growing data requirements for agentic AI.RAG emerged in the last couple of years to bec [...]

Match Score: 131.94

venturebeat
Phi-4 proves that a 'data-first' SFT methodology is the new differentiator

AI engineers often chase performance by scaling up LLM parameters and data, but the trend toward smaller, more efficient, and better-focused models has accelerated. The Phi-4 fine-tuning methodology [...]

Match Score: 127.08

venturebeat
Moonshot's Kimi K2 Thinking emerges as leading open source AI, outperforming GPT-5, Claude Sonnet 4.5 on key benchmarks

Even as concern and skepticism grows over U.S. AI startup OpenAI's buildout strategy and high spending commitments, Chinese open source AI providers are escalating their competition and one has e [...]

Match Score: 125.02

venturebeat
Databricks' Instructed Retriever beats traditional RAG data retrieval by 70% — enterprise metadata was the missing link

A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used a [...]

Match Score: 123.84

venturebeat
Meta's new structured prompting technique makes LLMs significantly better at code review — boosting accuracy to 93% in some cases

Deploying AI agents for repository-scale tasks like bug detection, patch verification, and code review requires overcoming significant technical hurdles. One major bottleneck: the need to set up dynam [...]

Match Score: 120.53

venturebeat
MiniMax-M2 is the new king of open source LLMs (especially for agentic tool calling)

Watch out, DeepSeek and Qwen! There's a new king of open source large language models (LLMs), especially when it comes to something enterprises are increasingly valuing: agentic tool use — that [...]

Match Score: 113.00