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Received — 25 July 2025 ⏭ Favourites
  • ✇InfoQ
  • State Space Models Can Enable AI in Low-Power Edge Computing Patrick Farry
    At the the 2025 Embedded Vision Summit, Tony Lewis, chief technology officer at BrainChip, presented research done by his company into state space models (SSMs) and how they can provide LLM capabilities with very low power consumption in limited computing environments, such as those found on dashcams, medical devices, security cameras, and even toys. By Patrick Farry
     
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State Space Models Can Enable AI in Low-Power Edge Computing

✇InfoQ
By: Patrick Farry
24 July 2025 at 22:00

At the the 2025 Embedded Vision Summit, Tony Lewis, chief technology officer at BrainChip, presented research done by his company into state space models (SSMs) and how they can provide LLM capabilities with very low power consumption in limited computing environments, such as those found on dashcams, medical devices, security cameras, and even toys.

By Patrick Farry
  • ✇Latest Science News -- ScienceDaily
  • A simple twist fooled AI—and revealed a dangerous flaw in medical ethics
    Even the most powerful AI models, including ChatGPT, can make surprisingly basic errors when navigating ethical medical decisions, a new study reveals. Researchers tweaked familiar ethical dilemmas and discovered that AI often defaulted to intuitive but incorrect responses—sometimes ignoring updated facts. The findings raise serious concerns about using AI for high-stakes health decisions and underscore the need for human oversight, especially when ethical nuance or emotional intelligence is inv
     
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A simple twist fooled AI—and revealed a dangerous flaw in medical ethics

✇Latest Science News -- ScienceDaily
24 July 2025 at 13:58
Even the most powerful AI models, including ChatGPT, can make surprisingly basic errors when navigating ethical medical decisions, a new study reveals. Researchers tweaked familiar ethical dilemmas and discovered that AI often defaulted to intuitive but incorrect responses—sometimes ignoring updated facts. The findings raise serious concerns about using AI for high-stakes health decisions and underscore the need for human oversight, especially when ethical nuance or emotional intelligence is involved.

PIVOT: an open-source tool for multi-omic spatial data registration

✇(Multiomics OR Omics) AND (Pancreatic)
By: André Forjaz · Valentina Matos Romero · Ian Reucroft · Margaret Eminizer · Donald Kramer · Daniela Higuera · Hengameh Mojdeganlou · Paola A Guerrero · Jimin Min · Meredith Wetzel · Dmitrijs Lvovs · Alens Valentin · Sarah M Shin · Xuan Yuan · Rosalie C Sears · Koei Chin · Anirban Maitra · Elana J Fertig · Won Jin Ho · Luciane T Kagohara · Laura D Wood · Denis Wirtz · Dimitrios N Sidiropoulos · Ashley L Kiemen
15 July 2025 at 18:00

bioRxiv [Preprint]. 2025 Jun 8:2025.06.08.658506. doi: 10.1101/2025.06.08.658506.

ABSTRACT

Advances in spatial profiling have resulted in the generation of multi-omic atlases that span biological scales. In general, multiple workflows are required for image registration, coordinate registration, and spot deconvolution to integrate modalities. To improve the throughput of registration of multi-omic cohorts, we introduce PIVOT, a user-friendly and open-source interface for streamlined nonlinear registration. We demonstrate PIVOT's strengths through registration of three multi-omic datasets, and show comparison of its performance to existing workflows.

PMID:40661390 | PMC:PMC12259011 | DOI:10.1101/2025.06.08.658506

Personalized molecular signatures of insulin resistance and type 2 diabetes

✇Cell
By: Jeppe Kjærgaard · Ben Stocks · John Henderson · Jordana B. Freemantle · David Rizo-Roca · Michele Puglia · Maria Madrazo Montoya · Daniel Andersson · Jesper Bäckdahl · Daniel Eriksson-Hogling · Jacob V. Stidsen · Michael Wierer · Simon Rasmussen · Kei Sakamoto · Kurt Højlund · Mikael Rydén · Juleen R. Zierath · Anna Krook · Atul S. Deshmukh
27 May 2025 at 08:00
Muscle samples from over 120 people were analyzed to identify molecular patterns linked to insulin resistance, a key feature of type 2 diabetes. The findings reveal new insights that could help tailor more personalized and effective treatments for the disease.
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