Sascha Brodsky

Science and Technology Journalist 

Recent Work


Beyond language: Why world models could be the next frontier for enterprise AI | IBM

IBM researchers have spent years building AI systems that simulate physical reality rather than just describing it. Now, some of the biggest names in the field are converging around that same idea, with billions of dollars riding on its potential.
When Turing Award winner Yann LeCun left Meta late last year to launch AMI Labs, a Paris-based startup devoted to building what he calls “world models,” he put a name and a funding round behind a critique that has been simmering in AI research circles...

The unbreakable man: Interview with Turing Award Winner Gilles Brassard

Brassard grew up in Montreal, obtained his doctorate in computer science from Cornell University in 1979, returned to the Canadian city, and has been at the Université de Montréal ever since, where he has held a full professorship since 1988 and a Canada Research Chair since 2001.
He is warm, slightly formal, fond of Bach and Mahler. He cooks. He goes to concerts in Amsterdam. The word he uses most often about his work is “fun.”
The idea for BB84 came from a paper. In 1976, while Brassard was st...

The AI ethics illusion | IBM

A chatbot will tell you that honesty matters.
Ask whether it is acceptable to lie to a coworker to avoid embarrassment, and the answer often arrives in calm, careful prose. The system may explain that honesty builds trust, that deception erodes relationships, that transparency helps organizations function. The response can read like the work of someone who has paused to weigh competing principles. But researchers say that impression can be misleading.
Two recent studies suggest that AI systems...

AI models at IBM and DeepMind are pushing DNA toward a GPT era | IBM

The human genome may be about to get its GPT moment.
Artificial intelligence is changing how scientists read DNA, with new models scanning long genetic sequences to link patterns in the code to biological behavior, from gene regulation to disease risk. IBM researchers say these approaches could reshape drug discovery over time, in ways that echo how AI has altered modern software development.
The stakes are enormous. Google DeepMind recently published its AlphaGenome model, which takes up to one...
IBM Think •

The scientific sprint: how AI is rewriting discovery timelines | IBM

A new breed of artificial intelligence threatens to upend centuries of scientific tradition by conducting experiments faster and at scales impossible for humans to match. While scientists have long relied on intuition, methodical research and painstaking trial and error, companies like Lila Sciences are now building what they call "Science Factories"—autonomous labs where AI systems generate hypotheses, design experiments and analyze results with minimal human intervention
IBM Blog •

The man who taught AI to learn believes human-level intelligence is closer than you think | IBM

Richard Sutton, one of the pioneers behind modern artificial intelligence, is not convinced that simply throwing more computing power at AI will lead to machines that think like humans. In fact, he argues today’s obsession with scaling up deep learning might be holding AI back from its full potential.
Sutton, alongside his longtime collaborator Andrew Barto, won this year’s Turing Award—often called the "Nobel Prize of Computing"—for his work in reinforcement learning. He believes the real brea...
IBM Blog •

Diffusion models challenge GPT as next-generation AI emerges | IBM

A new class of AI models is challenging the dominance of GPT-style systems, promising faster, cheaper and potentially more powerful alternatives.
Inception Labs, a startup founded by researchers from Stanford, recently released Mercury, a diffusion-based language model (dLLM) that refines entire phrases at once, rather than predicting words one by one. Unlike traditional large language models (LLMs), which use an autoregressive approach—generating one word at a time, based on the preceding text...
IBM Blog •

Beyond big models: Why AI needs more than just scale to reach AGI | IBM

The idea of artificial general intelligence—machines that can think, learn and reason as well as humans—has captivated scientists, entrepreneurs and science-fiction writers alike. Industry leaders like OpenAI’s Sam Altman and Google DeepMind’s Demis Hassabis suggest that AGI could be within reach, powered by the relentless scaling of neural networks. The thinking goes: the bigger the model, the smarter the AI.
But a new survey of AI experts reveals a growing skepticism of this idea. While today...
IBM Blog •

The scientific sprint: how AI is rewriting discovery timelines | IBM

The rise of scientific superintelligence raises profound questions about the future role of human scientists. Will AI eventually replace them? Or will it serve as a powerful collaborator enhancing human ingenuity?
IBM Principal Research Scientist Payel Das told IBM Think she believes AI will augment rather than replace human creativity. "The human-AI interaction remains central to turbocharging the discovery process," she says. "Human experts define the problem space and provide guidance, while...
IBM Think •

NVIDIA and IBM push AI agents into the enterprise fast lane | IBM

AI agents—autonomous systems powered by large language models (LLMs) that can take actions, call tools and interact with software—are no longer simply answering questions. They’re beginning to function more like digital coworkers.
NVIDIA recently introduced AI-Q and AgentIQ, a new open-source blueprint and toolkit aimed at helping businesses deploy multiple agents simultaneously to tackle complex problems. These tools are designed to enable agents to reason, plan and work together across softwa...
IBM Blog •

Pioneering reinforcement learning researcher contemplates AI's future | IBM

Reinforcement learning excels in video games and simulations but struggles in the real world. The problem? These systems learn by exploring different actions—a strength in virtual environments but a major risk in reality. "Exploration is both the biggest selling point of RL and its biggest limiting factor for real-world use," explains Riemer, highlighting why both researchers see this transition as a critical challenge.
"In the real-world, outside of simulation, exploration can lead to the agen...

DeepSeek shows there's room for more AI players | IBM

The AI arms race is no longer just for the billion-dollar giants.
Companies like OpenAI, Google and Microsoft have dominated the headlines when it comes to artificial intelligence conversation. However, a new wave of open-source innovation—exemplified by the recent DeepSeek model—is leveling the playing field. The model’s success underscores a growing trend: smaller firms can increasingly challenge AI’s most prominent players.
“This just reinforces things we already knew,” says David D. Cox, V...
IBM Blog •

Voice AI surge: How talking tech could reshape business - IBM Blog

Voice AI technology is rapidly evolving, promising to transform enterprise operations from customer service to internal communications.

In the last few weeks, OpenAI has launched new tools to simplify the creation of AI voice assistants and expanded its Advanced Voice Mode to more paying customers. Microsoft has updated its Copilot AI with enhanced voice capabilities and reasoning features, while Meta has introduced voice AI to its messaging apps.
Freethink Media •

Tesla's new self-driving software throws out its old code entirely

Tesla, the pioneering electric vehicle manufacturer known for its innovative and sometimes controversial approach to self-driving technology, has recently made a significant change to its Full Self-Driving (FSD) software. The company, led by Elon Musk, has decided to completely overhaul its existing FSD code, opting for a novel approach in the months leading up to the planned launch of its Robotaxi service.
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