Deep Nanometry (DNM) is an innovative technique combining high-speed optical detection with AI-driven noise reduction, allowing researchers to find rare nanoparticles like extracellular vesicles (EVs).
Since EVs play a role in disease detection, DNM could revolutionize early cancer diagnosis. Its applications stretch beyond healthcare, promising advances in vaccine research, and environmental science.
A Breakthrough in Nanoparticle Detection.
The biological cycle of our existence seems relatively straightforward: we’re born, we live, we die. The end.
But when you examine existence at the cellular level, things get a bit more interesting. You, me, and all of the 108 billion or so Homo sapiens who’ve ever walked the Earth have all been our own constellation of some 30 trillion cells. Each of our bodies is a collective organism of living human cells and microbes working in cooperation to create what our minds view as “life.” However, a growing number of new studies have found that, at least for some cells, death isn’t the end. Instead, it’s possibly the beginning of something new and wholly unexpected.
A growing snowball of research concerning a new class of AI-designed multicellular organisms known as “xenobots” is gaining scientific attention for their apparent autonomy. In September 2024, Peter Noble, Ph.D., a microbiologist from the University of Alabama at Birmingham, along with Alex Pozhitkov, Ph.D., a bioinformatics researcher at the City of Hope cancer center, detailed this research on the website The Conversation.
“Now the rise of AI is sparking a new discussion: If automation takes over more physical tasks and artificial intelligence takes over more intellectual ones, humans will be defined by their social abilities, said Raman.”
M doomed! 😜
The knowledge economy is on the way out, and a new economy is on the way for us humans at work, he said. I’m calling it the innovation economy.
In this new era, human innovation and our uniquely human skills, like social and emotional intelligence will be key, he added.
Skills such as creativity, curiosity, courage, compassion and communication — or the 5 C’s — are what underpin innovation, allowing us to come up with new ideas that challenge the status quo, collaborate, and ultimately build together, he said.
Anthropic, an artificial intelligence company founded by exiles from OpenAI, has introduced the first AI model that can produce either conventional output or a controllable amount of reasoning needed to solve more grueling problems.
Anthropic says the new hybrid model, called Claude 3.7, will make it easier for users and developers to tackle problems that require a mix of instinctive output and step-by-step cogitation. The user has a lot of control over the behavior—how long it thinks, and can trade reasoning and intelligence with time and budget, says Michael Gerstenhaber, product lead, AI platform at Anthropic.
Claude 3.7 also features a new scratchpad that reveals the model’s reasoning process. A similar feature proved popular with the Chinese AI model DeepSeek. It can help a user understand how a model is working over a problem in order to modify or refine prompts.
Dianne Penn, product lead of research at Anthropic, says the scratchpad is even more helpful when combined with the ability to ratchet a model’s reasoning up and down. If, for example, the model struggles to break down a problem correctly, a user can ask it to spend more time working on it.
Frontier AI companies are increasingly focused on getting the models to reason over problems as a way to increase their capabilities and broaden their usefulness. OpenAI, the company that kicked off the current AI boom with ChatGPT, was the first to offer a reasoning AI model, called o1, in September 2024.
OpenAI has since introduced a more powerful version called o3, while rival Google has released a similar offering for its model Gemini, called Flash Thinking. In both cases, users have to switch between models to access the reasoning abilities—a key difference compared to Claude 3.7.
A robotic arm that moves with nothing but the power of thought—a concept that once seemed like pure science fiction is now at the heart of Neuralink’s latest breakthrough. The brain-chip company, founded by Elon Musk, has unveiled an ambitious project that aims to connect its neural implant, the N1, to an experimental robotic limb, potentially transforming the lives of people with paralysis.
Identifying and delineating cell structures in microscopy images is crucial for understanding the complex processes of life. This task is called “segmentation” and it enables a range of applications, such as analyzing the reaction of cells to drug treatments, or comparing cell structures in different genotypes.
It was already possible to carry out automatic segmentation of those biological structures, but the dedicated methods only worked in specific conditions and adapting them to new conditions was costly. An international research team led by Göttingen University has now developed a method for retraining the existing AI-based software Segment Anything on over 17,000 microscopy images with over 2 million structures annotated by hand.
The new model is called Segment Anything for Microscopy and it can precisely segment images of tissues, cells and similar structures in a wide range of settings. To make it available to researchers and medical doctors, they have also created μSAM, user-friendly software to “segment anything” in microscopy images. The work is published in Nature Methods.
I wondered when this would start!
“This means that should everything go according to plan, the humanoid robot will eventually be put to work building itself.” 🤖 🤖
Apptronik, an Austin-based maker of humanoid robots, on Tuesday announced a new pilot partnership with American supply chain/manufacturing stalwart, Jabil. The deal arrives two weeks after Apptronik announced a $350 million Series A financing round aimed at scaling up production of its Apollo robot.
The Jabil deal is the second major pilot announced by Apptronik. It follows a March 2024 partnership that put Apollo to work on the Mercedes-Benz manufacturing floor. While the company tells TechCrunch that its partnership with the automaker is ongoing, it has yet to graduate beyond the pilot stage.
In addition to test running the humanoid robot on its factory floor, this new deal also finds Florida-based Jabil and Apptronik becoming manufacturing partners. Once Apollo is determined to be commercially viable, Jabil will begin producing the robot in its own factories. This means that should everything go according to plan, the humanoid robot will eventually be put to work building itself.
The prospect of consciousness in artificial systems is closely tied to the viability of functionalism about consciousness. Even if consciousness arises from the abstract functional relationships between the parts of a system, it does not follow that any digital system that implements the right functional organization would be conscious. Functionalism requires constraints on what it takes to properly implement an organization. Existing proposals for constraints on implementation relate to the integrity of the parts and states of the realizers of roles in a functional organization. This paper presents and motivates three novel integrity constraints on proper implementation not satisfied by current neural network models.