thenextweb
I built a machine learning model to predict who leaves tech jobs early. The results surprised me.

I went into this research convinced I already knew the answer. After more than a decade in People Analytics, the last few years at Meta, I had a working theory about why tech employees leave their jobs within the first year. Two things, I believed, were doing most of the damage: whether someone was getting […]<br /> This story continues at The Next Web [...]

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Destination
Valve's Steam Machine launches in 2026: Everything we know so far

The Steam Machine is back from the dead. Not as a Valve-supported program for manufacturers to create living room PCs, but instead as a home console sibling to the Steam Deck. Valve introduced its sec [...]

Match Score: 91.56

Destination
Everything we know about Valve's new Steam Machine

The Steam Machine is back from the dead. Not as a Valve-supported program for manufacturers to create living room PCs, but instead a home console sibling to the Steam Deck. Valve introduced its second [...]

Match Score: 76.82

venturebeat
Fundamental emerges from stealth with first major foundation model trained for tabular data

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital canv [...]

Match Score: 54.12

venturebeat
Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

The deep learning revolution has a curious blind spot: the spreadsheet. While Large Language Models (LLMs) have mastered the nuances of human prose and image generators have conquered the digital canv [...]

Match Score: 54.12

blogspot
How I Get Free Traffic from ChatGPT in 2025 (AIO vs SEO)

Three weeks ago, I tested something that completely changed how I think about organic traffic. I opened ChatGPT and asked a simple question: "What's the best course on building SaaS with Wor [...]

Match Score: 54.09

venturebeat
MIT's new fine-tuning method lets LLMs learn new skills without losing old ones

When enterprises fine-tune LLMs for new tasks, they risk breaking everything the models already know. This forces companies to maintain separate models for every skill.Researchers at MIT, the Improbab [...]

Match Score: 50.98

venturebeat
Upwork study shows AI agents excel with human partners but fail independently

Artificial intelligence agents powered by the world's most advanced language models routinely fail to complete even straightforward professional tasks on their own, according to groundbreaking re [...]

Match Score: 49.17

venturebeat
Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

As agentic AI workflows multiply the cost and latency of long reasoning chains, a team from the University of Maryland, Lawrence Livermore National Labs, Columbia University and TogetherAI has found a [...]

Match Score: 48.10

venturebeat
Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after trai [...]

Match Score: 46.81