Robotics/AI – Lifeboat News: The Blog

Apr 6
2026

Targeting metabolism to combat anticancer and antibacterial drug resistance

Combating anticancer and antibacterial drug resistance by metabolic targeting.

Bacteria and cancer cells activate defense mechanisms driven by central carbon and amino acid metabolism to overcome drug-induced stress.

Drug tolerance and persistence are driven by a dormant state in bacteria, whereas cancer cells upregulate energy metabolism to withstand prolonged drug exposure.

Biofilms, granulomas, and the tumor microenvironment share hypoxic and acidic conditions, where cells rely on anaerobic and lipid metabolism for survival.

Macrophage immunometabolism influences disease progression in tuberculosis and cancer. Common approaches for overcoming drug resistance include blocking metabolic targets that enhance drug lethality and synergistic drug combinations.

Drug repurposing, dietary interventions, and immunotherapy have shown use in cancer, but their antibacterial potential remains underexplored. sciencenewshighlights ScienceMission https://sciencemission.com/Targeting-metabolism-to-combat-anticancer

Continue reading “Targeting metabolism to combat anticancer and antibacterial drug resistance” | >

Apr 5
2026

Natural protein sequences represent only a fraction of what’s theoretically possible

The limitations imposed by evolution have implications for AI tools trained on existing sequences and de novo protein design

Apr 5
2026

Beyond the AI Hype: When Will We Know We’ve Reached AGI?

When NVIDIA founder and CEO Jensen Huang told podcaster Lex Fridman in a recent interview that he thinks we have already achieved AGI, I understood why the statement landed with such force. Today’s systems are impressive, useful, and often psychologically persuasive. They can create the feeling that the threshold has already been crossed. But my answer is no: we have not achieved AGI just yet. In my 2026 book, SUPERALIGNMENT: The Three Approaches to the AI Alignment Problem — How to Ensure the Arrival of Benevolent Artificial Superintelligence Aligned with Human Goals and Values, I argue that AGI should not be declared based on hype, surprise, or market excitement. It should be recognized only when three far more meaningful benchmarks are met.

In fact, one of the reasons this debate keeps spiraling into confusion is that we have been trapped for years in the “moving goalposts” problem. By practical conversational standards, machines passed the Turing test long ago. But every time AI masters a previously “human-exclusive” capacity—dialogue, strategy, writing, even emotional style—many observers simply redefine that achievement as mere automation. That is precisely why I reject unstable, psychology-based thresholds. If our benchmark is just whatever still makes humans feel uniquely special, then AGI will always remain one step away by definition.

That is why, in SUPERALIGNMENT, I start with operational definitions of AGI and ASI. For me, AGI is not merely a system that performs well across many cognitive tasks. It is a system that can generalize knowledge across domains, reason abstractly, adapt to open and uncertain environments, transfer learned knowledge to novel contexts, and introspect on its own reasoning. In other words, AGI is not just impressive breadth. It is flexible, self-reflective generality at par with or above human capabilities. That is a much higher bar than what most people mean when they casually say, “AI is already general.”

Apr 5
2026

Studies on animal minds suggest consciousness is not computation

We’re often seduced by the idea that the mind is a computer, and that consciousness is just a matter of running the right code. But philosopher Peter Godfrey-Smith, renowned for his work on octopus minds, disagrees. Fresh research into animal minds—from bees to jellyfish—suggests that consciousness arises not from software but from electrical oscillations moving rhythmically across cell membranes in living brains. And those oscillations, Godfrey-Smith argues, are unlikely to be reproducible in artificial hardware. Perhaps, then, only living brains can truly be conscious.

Late in the previous century, there seemed to be good reasons to think that the physical make-up of a system could not matter much to whether that system had a mind. The organization of the system is what matters, people thought, and physically different systems can be organized the same way. As a result, artificial minds making use of ordinary computer hardware should be possible. This whole discussion was hypothetical, because there weren’t any convincing possible cases of artificial minds to worry about.

Since then, two things have happened. From around 2022, we’ve been confronted with candidates for artificial minds that are disturbingly impressive. These are the LLM systems, such as ChatGPT. But reasons have emerged to doubt that the physical make-up of a system is irrelevant and minds are “substrate independent.” A view sometimes called biological naturalism holds that the biological details of nervous systems might make a difference to whether a physical system has a mind. (The term was coined, with this sense at least, by John Searle.) But if nervous systems and brains are special, what is it that makes them special?

Apr 5
2026

Scientists Discover Strange Property of Rice and Turn It Into a Smart Material

Rice behaves in an unexpected way under pressure. When compressed quickly, it becomes weaker, but under slow pressure it stays strong. This insight is helping scientists develop a new material that could be used in “soft” robots that automatically adjust stiffness, as well as protective gear that responds to how fast an impact occurs.

Using this property, researchers created a new type of “metamaterial,” an engineered structure designed to exhibit behaviors not found in natural materials.

Apr 4
2026

Embodiment in multimodal large language models

Kadambi et al. propose a dual-embodiment framework for multimodal large language models based on internal and external embodiment. Such biologically inspired principles may help inform next-generation AI systems.

Apr 4
2026

Researchers 3D print robot the size of a single-cell organism — devices move and navigate even without a ‘brain,’ uses their shape and the environment to get going

These robots are smaller than a strand of human hair but can move independently even without a motor and sensors.

Apr 4
2026

MICrONS Explorer: A virtual observatory of the cortex

The Machine Intelligence from Cortical Networks (MICrONS) program seeks to revolutionize machine learning by reverse-engineering the algorithms of the brain. It is an ambitious program to map the function and connectivity of cortical circuits, using high throughput imaging technologies, with the goal of providing insights into the computational principles that underlie cortical function in order to advance the next generation of machine learning algorithms.

This website serves as a data portal to release connectivity and functional imaging data collected by a consortium of laboratories led by groups at the Allen Institute for Brain Science, Princeton University, and Baylor College of Medicine, with support from a broad array of teams, coordinated and funded by the IARPA MICrONS program. These data include large scale electron microscopy based reconstructions of cortical circuitry from mouse visual cortex, with corresponding functional imaging data from those same neurons.

Have a Scientific Request? Check out the Virtual Observatory of the Cortex (VORTEX) project, a BRAIN Initiative funded program to bring the MICrONS dataset to the research community. Access proofreading resources to answer your scientific questions.

Apr 4
2026

Reconstructing tumor tissues in 3D: From organoids to bioengineered niches

Tumor tissue engineering has opened new avenues for cancer research. With an emphasis on gastrointestinal malignancies, we summarize capabilities and limitations of patient-derived and engineered organoid models. We then discuss how innovations in biomaterial design, biofabrication, microfluidics, benchmarking, and AI converge to better emulate tumor tissues and advance translational modeling.

Apr 4
2026

Get access to all the best AI models in one place at Mammouth

https://mammouth.ai.

Timestamps:
00:00 — New Way Of Computing
06:46 — How It Works
09:39 — Outlook.

My Podcast on Apple: https://podcasts.apple.com/at/podcast… Podcast on Spotify: https://open.spotify.com/show/3drr7A8… Let’s connect on LinkedIn: / anastasiintech Newsletter: https://anastasiintech.substack.com Instagram: / anastasi.in.tech Patreon: / anastasiintech.

Let’s connect on LinkedIn: / anastasiintech
Newsletter: https://anastasiintech.substack.com
Instagram: / anastasi.in.tech
Patreon: / anastasiintech.