The AI race is shifting from bigger models to cheaper, smarter systems

AI companies are moving beyond a simple race over who has the biggest or newest model. Perplexity CEO Aravind Srinivas says ...

Fine‑Tuned SLMs: A New Operating Model For Enterprise AI

Enterprise AI is at an inflection point. What began with centralized, cloud-scale large language models (LLMs) is moving ...

Data readiness is the new quant bottleneck

At Bloomberg’s Technology and Innovation Forum in Singapore, the most useful conversation about quant research did not start ...
TechCrunch

Making AI models ‘forget’ undesirable data hurts their performance

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...
TechCrunch

The promise and perils of synthetic data

Is it possible for an AI to be trained just on data generated by another AI? It might sound like a harebrained idea. But it’s one that’s been around for quite some time — and as new, real data is ...
The Economist

Training AI models might not need enormous data centres

Once, the world’s richest men competed over yachts, jets and private islands. Now, the size-measuring contest of choice is clusters. Just 18 months ago, OpenAI trained GPT-4, its then state-of-the-art ...

Liquid AI's smallest model yet LFM2.5-230M beats models 4X its size at data extraction, can run 'anywhere'

LFM2.5-230M proves that while 3-billion-parameter models like VibeThinker are solving advanced calculus, a 230-million-parameter model is the superior, highly optimized choice for executing structured ...
Campus Technology

Top Actions to Achieve a Future of Unified Data Models in Higher Ed

As institutions become more data-rich and data-reliant, their capacity for analytics is not necessarily keeping up. In an Educause QuickPoll of higher education IT leadership focused on data strategy ...