Destination
Deep Cogito Raises $43M Series A to Build the Post-Training Engine for Self-Improving AI

Deep Cogito has raised a $43 million Series A as the San Francisco AI lab looks to scale an increasingly important part of the artificial intelligence stack: what happens after a foundation model has already been pre-trained. The round was led by TQ Ventures, with participation from Benchmark, Nexus Venture Partners, Atreides Management, South Park Commons, and cloud security company Zscaler, which is both a customer and strategic investor. The financing brings Deep Cogito's total funding to… [...]

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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: 112.47

venturebeat
Meta researchers introduce 'hyperagents' to unlock self-improving AI for non-coding tasks

Creating self-improving AI systems is an important step toward deploying agents in dynamic environments, especially in enterprise production environments, where tasks are not always predictable, nor c [...]

Match Score: 100.13

venturebeat
Baseten takes on hyperscalers with new AI training platform that lets you own your model weights

Baseten, the AI infrastructure company recently valued at $2.15 billion, is making its most significant product pivot yet: a full-scale push into model training that could reshape how enterprises wean [...]

Match Score: 88.15

qz
Deep Cogito raised $43M to build AI models that teach themselves to improve

TQ Ventures led the round, with Benchmark, Nexus Venture Partners, and cybersecurity firm Zscaler among the participants [...]

Match Score: 82.44

venturebeat
Why your LLM bill is exploding — and how semantic caching can cut it by 73%

Our LLM API bill was growing 30% month-over-month. Traffic was increasing, but not that fast. When I analyzed our query logs, I found the real problem: Users ask the same questions in different ways.& [...]

Match Score: 77.77

venturebeat
Black Forest Labs' new Self-Flow technique makes training multimodal AI models 2.8x more efficient

To create coherent images or videos, generative AI diffusion models like Stable Diffusion or FLUX have typically relied on external "teachers"—frozen encoders like CLIP or DINOv2—to prov [...]

Match Score: 67.56

venturebeat
Nimble claims its new, domain-specialized Web Search Agents cut token costs in half while boosting retrieval accuracy

Nimble, a New York City-based tech startup VentureBeat previously covered for its efforts to re-invent web search for enterprises by using multiple AI agents to improve accuracy and depth, is taking a [...]

Match Score: 66.34

venturebeat
Mistral AI launches Forge to help companies build proprietary AI models, challenging cloud giants

Mistral AI on Monday launched Forge, an enterprise model training platform that allows organizations to build, customize, and continuously improve AI models using their own proprietary data — a move [...]

Match Score: 63.98

venturebeat
Self-improving language models are becoming reality with MIT's updated SEAL technique

Researchers at the Massachusetts Institute of Technology (MIT) are gaining renewed attention for developing and open sourcing a technique that allows large language models (LLMs) — like those underp [...]

Match Score: 61.36