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What is the #KempnerInstitute? Watch a short video feature to dive deeper into our mission and meet the researchers behind it: bit.ly/49ODO2K #AI #ML #NeuroAI #neuroscience @Harvard
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⚡NEW: Unlocking lossless speedups in LLMs via discrete diffusion. A new diffusion-augmented model, Uno, combines autoregressive and diffusion weights in one network to generate multiple tokens per forward pass. More in today’s Deeper Learning blog post: bit.ly/4AmooR0
kempnerinstitute.harvard.edu Unlocking Lossless Speedups in LLMs via Discrete Diffusion - Kempner Institute Large language models generate text one token at a time, which makes inference slow. Diffusion language models generate many tokens in parallel, but they lose quality, and their speedups fade […] A team led by #KempnerInstitute Associate Faculty @marinkazitnik has recieved a Cancer Grand Challenges grant to create AI “co-scientists” that help researchers analyze data, generate hypotheses, and suggest new experiments, speeding new knowledge and therapies. Learn more:
Our cancer researchers are putting AI to the test.
Three Cancer Grand Challenges teams have been selected as part of a $10M project to explore how AI co-scientists could accelerate cancer research 🚀
Led by @marinkazitnik (@harvardmed), Project AURORA is developing AI co-scientists to work alongside researchers, helping them generate scientific hypotheses and prioritise experiments.
Following a competitive application and selection process, researchers from three currently funded Cancer Grand Challenges teams have been selected as our AURORA pioneer teams. They will be led by:
🔹@NickyMcGranahan (team NexTGen)
🔹Welles Robinson and @squezadd (team MATCHMAKERS)
🔹@nlbigas (team PROMINENT)
We’re excited to see how this project can help our scientists make faster progress against cancer’s toughest challenges!
Learn more about AURORA and the pioneer teams ➡️ bit.ly/4yXS4Tz
AURORA is funded by @CR_UK through Cancer Grand Challenges.View quoted post on X
At #CoRL this week? Check out the workshop on Memory for Robot Foundation Models with #KempnerInstitute panelist @du_yilun! @pgozdil
Heading to Austin for my FIRST #CoRL! 🙂 Excited to meet fellow robotics researchers, DM me if you'd like to chat! We're organizing a workshop on Memory for Robot Foundation Models. All accepted papers and the workshop program are now online 👉 corl2026-memory.github.io #CoRL2026View quoted post on X
🔍What if we could anticipate which scenarios LLMs will fail on and focus on those? Adversarial Concept Search predicts when a model might make a mistake using representational geometry. More in today's Deeper Learning blog post from the #KempnerInstitute: bit.ly/4ePWsfW
kempnerinstitute.harvard.edu Adversarial Concept Search: Predicting Compositional Errors From Feature Geometry - Kempner... Adversarial Concept Search (ACS) identifies meaningful conceptual scenarios that are likely to induce model failure without evaluating the model on specific inputs that instantiate those scenarios....