Michael Levin dives deep into the intersection of biology and artificial intelligence, exploring how individual units—whether cells or humans—can form cohesive, goal-driven systems.
Sharing insights into \.
Category: biological – Page 3
Google Just Dropped The Singularity Bomb
Google DeepMind’s Demis Hassabis says humanity may already be standing in the foothills of the singularity. AI agents are now coding, researching, planning, paying, helping with science, and cutting real work from days to minutes. The big question is no longer whether AI is perfect. It’s whether imperfect AI has already become useful enough to speed up everything around it.
📩 Brand Deals \& Partnerships: [email protected].
✉ General Inquiries: [email protected].
🚀 New Channel: / @space.revolution.
📌 What You’ll See:
Google DeepMind’s warning that we are entering the foothills of the singularity.
SOURCE: https://www.axios.com/2026/05/26/deep… new Gemini for Science tools built to speed up scientific discovery SOURCE: https://blog.google/innovation-and-ai… AWS letting autonomous AI agents make payments and complete transactions SOURCE: https://aws.amazon.com/about-aws/what… AxiomProver helping prove new math results in Lean and Mathlib SOURCE: https://arxiv.org/abs/2602.05090 Biohub’s new world model of protein biology trained across billions of sequences SOURCE: https://biohub.ai/esm/protein ARC-AGI-3 showing the huge gap between today’s frontier AI and human reasoning SOURCE: https://aiforautomation.io/news/2026-… 🚨 Why It Matters This is bigger than another AI model update. Google DeepMind is now openly talking about the singularity, while AI agents are already starting to speed up coding, science, business, and research. Some experts think AGI may be closer than expected, while others say current AI still lacks true intelligence. Either way, the AI race is shifting fast from chatbots into agents that can plan, act, build, discover, and change real workflows. #google #singularity #ai.
Google’s new Gemini for Science tools built to speed up scientific discovery.
SOURCE: https://blog.google/innovation-and-ai…
AWS letting autonomous AI agents make payments and complete transactions.
SOURCE: https://aws.amazon.com/about-aws/what…
AxiomProver helping prove new math results in Lean and Mathlib.
SOURCE: https://arxiv.org/abs/2602.05090
Biohub’s new world model of protein biology trained across billions of sequences.
SOURCE: https://biohub.ai/esm/protein.
ARC-AGI-3 showing the huge gap between today’s frontier AI and human reasoning.
SOURCE: https://aiforautomation.io/news/2026-…
🚨 Why It Matters.
This is bigger than another AI model update. Google DeepMind is now openly talking about the singularity, while AI agents are already starting to speed up coding, science, business, and research. Some experts think AGI may be closer than expected, while others say current AI still lacks true intelligence. Either way, the AI race is shifting fast from chatbots into agents that can plan, act, build, discover, and change real workflows.
#google #singularity #ai
Conversation with Nic Rouleau, part 1: “Some thoughts on the mind as material”
This is a ~1 hour talk and discussion, comprising part 1 of a conversation with a really interesting young neuroscientist, as well as friend, collaborator, and our Center member, Nicolas Rouleau (https://allencenter.tufts.edu/nicolas… goes over unconventional aspects of neuroscience touching on free will, cybernetics, consciousness, and a lot more. We start a discussion which is continued in part 2. For more information:
Nic’s website: www.rouleaulab.com.
X account: @DrNRouleau.
Recent papers to check out:
Sellar, E.P., Rouleau, N. (In Review). A cybernetic framework for synthetic biological intelligence in the era of neural tissue engineering. Preprint doi: 10.31234/osf.io/md2wf_v1.
Kansala, C., Cicek, E., Nkansah-Okoree, V., Golding, A., Murugan, N.J., Rouleau, N. (In Review). Superstitious conditioning forms the experience of free will under causal determinism. Preprint doi: 10.31234/osf.io/fk3yt_v2.
Roskies, A. \& Rouleau, N. (Forthcoming, In Press). Research on brain organoids should prioritize questions of agency, not consciousness. AJOB Neuroscience.
Scientists Create the First Artificial Neuron That Can Communicate
A major breakthrough in artificial intelligence may have arrived: scientists have created an artificial neuron capable of communicating with other neurons.
Inspired by the human brain, this technology could allow machines to process information in a far more biological and efficient way. Instead of traditional computing architectures, future systems could operate more like living neural networks.
In this video we explore how artificial neurons work, why this breakthrough matters, and how it could reshape AI, robotics, and neuroscience.
#ArtificialNeuron, #ArtificialIntelligence, #Neuroscience, #FutureTechnology, #AIResearch, #NeuralNetworks
Single-step 8-9x expansion reveals nanoscale centrioles without electron microscopy
In a study published in ACS Nano, researchers from National Taiwan University report a new expansion microscopy strategy termed high-fold homogeneous expansion microscopy (hiHomoExM), capable of achieving approximately 8–9× isotropic expansion in a single expansion step while preserving delicate ultrastructural organization.
Expansion microscopy works by embedding biological samples within a swellable polymer hydrogel. Following chemical processing, the hydrogel expands uniformly in water, physically separating biomolecules and effectively increasing the spatial resolution achievable by conventional light microscopes.
“To achieve nanoscale imaging faithfully, both high expansion and homogeneous specimen preservation are essential,” explains the research team. “Nonuniform expansion can distort ultrastructural information and limit biological interpretation.”
MIT researchers use AI to uncover atomic defects in materials
In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during the manufacturing process of products like steel, semiconductors, and solar cells to help improve strength, control electrical conductivity, optimize performance, and more.
But even as defects have become a powerful tool, accurately measuring different types of defects and their concentrations in finished products has been challenging, especially without cutting open or damaging the final material. Without knowing what defects are in their materials, engineers risk making products that perform poorly or have unintended properties.
Now, MIT researchers have built an AI model capable of classifying and quantifying certain defects using data from a noninvasive neutron-scattering technique. The model, which was trained on 2,000 different semiconductor materials, can detect up to six kinds of point defects in a material simultaneously, something that would be impossible using conventional techniques alone.
Brain Cells Master Doom: Cortical Labs’ Biological Computer Reaches Major AI Milestone
Flowgrammer.ca -＞ https://flowgrammer.ca/
AI News and Resources -＞ https://flowgrammers.ca.
OpenClaw Toronto -＞ https://openclawto.com/
Cut Costs. Boost Output. Stay Ahead.
If smarter systems can learn faster with less energy, imagine what your business can do with the right automation. Flowgrammer helps you eliminate repetitive work, reduce operational drag, and scale without hiring headaches.
Book Your Free Automation Audit.
https://flowgrammer.ca/
Startup Investor Drinks Toronto — https://startupdrinksto.com/
Toronto’s Startup Community — https://torontostarts.com/
Silicon Scoop.
Silicon Scoop Podcast — https://torontostarts.com/silicon-scoop/
Apple: https://podcasts.apple.com/us/podcast…
Spotify: https://open.spotify.com/show/5bAzF0M…
YouTube: • Silicon Scoop.
Startup Talk.
Novel porous gel changes color, shrinks and hardens when it detects target molecules
Researchers at Kyoto University and Tohoku University have developed a new porous polymer gel that selectively recognizes specific molecules (referred to as “guests” in the study) through coordination chemistry and converts these invisible molecular-scale interactions into strikingly visible, macroscale deformation.
The study demonstrates how subtle differences in molecular structure can directly alter the shape, color, and mechanical properties of a soft material, opening new possibilities for “smart” stimuli-responsive materials and molecularly programmable soft matter that can sense and react to its environment.
Molecular recognition is a central concept in supramolecular chemistry and biology, where molecules selectively interact through precisely arranged chemical interactions. While most artificial molecular recognition systems rely on noncovalent interactions such as hydrogen bonding, the present study instead exploits coordination interactions —a type of chemical “handshake”—between metal centers and electron-rich guest molecules.
How schizophrenia risk may begin: Gene changes reshape signaling in developing neurons
Researchers at King’s College London have identified the biological nature and timing of changes in human cortical neurons caused by altering activity of a schizophrenia-associated gene in developing human neurons. This discovery links a genetic risk factor to cellular changes in neurons; an essential step for understanding the neurobiology of this mental illness and developing future treatments.
Schizophrenia is estimated to be one of the most heritable psychiatric conditions, with a strong developmental aspect. Large-scale human genomic studies have identified many genetic variants which are thought to increase the likelihood of schizophrenia.
However, the link between these genetic risk variants and the underlying neurobiology of schizophrenia is less well understood. Addressing this knowledge gap provides vital information that could ultimately help develop therapies for the disorder.