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Google's Gemini is available to consumers in Bard or Pixel 8 Pro now, with an enterprise model coming Dec. 13. Get more details about the LLM. Gemini is available to consumers in Bard or Pixel 8 Pro now, with an enterprise model coming Dec. 13. Google has revealed Gemini, its long-rumored large language model and rival to GPT-4. Global users of Google Bard and the Pixel 8 Pro will be able to run Gemini starting now; an enterprise product, Gemini Pro, is coming on Dec. 13. Developers can sign up now for an early preview in Android AICore. Jump to: What is Gemini?Gemini is a large language model that runs generative artificial intelligence applications; it can summarize text, create images and answer questions. Gemini was trained on Google’s Tensor Processing Units v4 and v5e. Google’s Bard is a generative AI based on the PaLM large language mode. Starting today, Gemini will be used to give Bard “more advanced reasoning, planning, understanding and more,” according to a Google press release. SEE: Microsoft invested $3.2 billion on AI in the UK. (TechRepublic) Gemini size optionsGemini comes in three model sizes: Ultra, Pro and Nano. Ultra is the most capable, Nano is the smallest and most efficient, and Pro sits in the middle for general tasks. The Nano version is what Google is using on the Pixel, while Bard gets Pro. Google says it plans to run “extensive trust and safety checks” before releasing Gemini Ultra to select groups. Gemini for codingGemini can code in Python, Java, C++, Go and other popular programming languages. Google used Gemini to upgrade Google’s AI-powered code generation system, AlphaCode. Gemini will be added to more Google productsNext, Google plans to bring Gemini to Ads, Chrome and Duet AI. In the future, Gemini will be used in Google Search as well. Competitors to GeminiGemini and the products built with it, such as chatbots, will compete with OpenAI’s GPT-4, Microsoft’s Copilot (which is based on OpenAI’s GPT-4), Anthropic’s Claude AI, Meta’s Llama 2 and more. Google claims Gemini Ultra outperforms GPT-4 in several benchmarks, including the massive multitask language understanding general knowledge test and in Python code generation. Does Gemini have an enterprise product?Starting Dec. 13, enterprise customers and developers will be able to access Gemini Pro through the Gemini API in Google’s Vertex AI or Google AI Studio. Google expects Gemini Nano to be generally available for developers and enterprise customers in early 2024. Android developers can use this LLM to build Gemini apps on-device through AndroidAICore. Possible enterprise use cases for GeminiMore must-read AI coverageOf particular interest to enterprise use cases might be Gemini’s ability to “understand and reason about users’ intent,” said Palash Nandy, engineering director at Google, in a demonstration video. Gemini generates a bespoke UI depending on whether the user is looking for images or text. In the same UI, Gemini will flag areas in which it doesn’t have enough information and ask for clarification. Through the bespoke UI, the user can explore other options with increasing detail. Gemini has been trained on multimodal content from the very beginning instead of starting with text and expanding to audio, images and video later, letting Gemini parse written or visual information with equal acuity. One example of how this might be useful for business Google provides is the prompt “Could Gemini help make a demo based on this video?” in which the AI translates video content to an original animation. Gemini’s timing compared to other popular LLMsGemini has been hotly rumored, as Google tries to compete with OpenAI. The New York Times reported Google executives were “shaken” by OpenAI’s tech in January 2023. More recently, Google supposedly struggled with releasing Gemini in languages other than English, leading to a delay of an in-person launch event. However, releasing Google’s own large language model after ChatGPT has received gradual GPT-4 powered updates for nearly a year means Google has the advantage of leapfrogging the last year of AI development. For example, Gemini is multimodal (i.e., able to work with text, video, speech and code) and lives natively on the Google Pixel 8. Users can access Gemini on their Google Pixel 8 without an internet connection, unlike ChatGPT, which started out in a browser.
Read the full article at: www.techrepublic.com
Via Charles Tiayon
The Chinese government will accelerate the widespread production of advanced humanoid robots by funding more startups in the robotics field. Fourier Intelligence China is hoping to welcome robotkind in just two years’ time. The country plans to produce its first humanoid robots by 2025, according to an ambitious blueprint published by the Ministry of Industry and Information (MITT) Technology last week. The MITT says the advanced bipedal droids have the power to reshape the world, carrying out menial, repetitive tasks in farms, factories, and houses to alleviate our workload. “They are expected to become disruptive products after computers, smartphones, and new energy vehicles,” the document states.The government will accelerate the development of the robots by funding more young companies in the field, as reported by Bloomberg. Fourier Intelligence is one such Chinese startup hoping to start mass-producing general-purpose humanoid robots by the end of this year. The Fourier GR-1 measures five feet and four inches and weighs around 121 pounds. With 40 joints, the bot reportedly has “unparalleled agility” human-like movement. It can also walk at roughly 3 mph and complete basic tasks. China isn’t the only country working on our future robot helpers, of course. In the U.S., Tesla is continuing to refine Optimus. The bipedal humanoid robot has progressed rapidly since the first shaky prototype was revealed at the marque’s AI day in 2022. It can now do yoga, in fact. Tesla has yet to announce a firm timetable for when Optimus will hit the market, but CEO Elon Musk has previously said that the $20,000 robot could be ready in three to five years. Agility Robotics is another U.S. company with “building robots for good.” It opened a robot manufacturing facility in Oregon earlier this year that can produce more than 10,000 Digit droids per year. It also recently announced that Amazon will begin testing Digit for use in their operations. Meanwhile, Boston Dynamics—makers of Spot, the $75,000 robotic dog—has built another decidedly agile bipedal robot. Atlas showed it could move various obstacles earlier this year, after nailing a parkour course in 2021. Boston Dynamic’s Atlas is a research platform and not available for purchase, but the robot does show the U.S. is on par with China in terms of droid design. Read the full article at: robbreport.com
Via Dr. Stefan Gruenwald
The landmark decision could transform the treatment of sickle-cell disease and β-thalassaemia — but the technology is expensive. In a world first, the UK medicines regulator has approved a therapy that uses the CRISPR–Cas9 gene-editing tool as a treatment. The decision marks another high point for a biotechnology that has been lauded as revolutionary in the decade since its discovery. The therapy, called Casgevy, will treat the blood conditions sickle-cell disease and β-thalassaemia. Sickle-cell disease, also known as sickle-cell anaemia, can cause debilitating pain, and people with β-thalassaemia often require regular blood transfusions. “This is a landmark approval which opens the door for further applications of CRISPR therapies in the future for the potential cure of many genetic diseases,” said Kay Davies, a geneticist at the University of Oxford, UK, in comments to the UK Science Media Centre (SMC). Nature magazine explains the research behind the treatment and explores what’s next. What research led to the approval? The approval by the Medicines and Healthcare products Regulatory Agency (MHRA) follows promising results from clinical trials that tested a one-time treatment, which is administered by intravenous infusion. The therapy was developed by the pharmaceutical company Vertex Pharmaceuticals in Boston, Massachusetts, and biotechnology company CRISPR Therapeutics in Zug, Switzerland. The trial for sickle-cell disease has followed 29 out of 45 participants long enough to draw interim results. Casgevy completely relieved 28 of those people of debilitating episodes of pain for at least one year after treatment. Researchers also tested the treatment for a severe form of β-thalassaemia, which is conventionally treated with blood transfusions roughly once a month. In this trial, 54 people received Casgevy, of which 42 participated for long enough to provide interim results. Among those 42 participants, 39 did not need a red-blood-cell transfusion for at least one year. The remaining three had their need for blood transfusions reduced by more than a 70%. Read the full article at: www.nature.com
Via Dr. Stefan Gruenwald
For the first time, scientists have demonstrated that the brain’s electrical activity can be decoded and used to reconstruct music.
Artificial intelligence has turned the brain’s electrical signals into somewhat garbled classic rock"
"Neuroscientists have reconstructed recognizable audio of a 1979 Pink Floyd song by using machine learning to decode electrical activity in the brains of listeners. As study participants undergoing surgery listened to “Another Brick in the Wall (Part 1),” electrodes placed on the surface of the brain captured the activity of regions attuned to the song’s acoustic profile. "
Neuroscientists have worked for decades to decode what people are seeing, hearing or thinking from brain activity alone. In 2012 a team that included the new study’s senior author—cognitive neuroscientist Robert Knight of the University of California, Berkeley—became the first to successfully reconstruct audio recordings of words participants heard while wearing implanted electrodes. Others have since used similar techniques to reproduce recently viewed or imagined pictures from participants’ brain scans, including human faces and landscape photographs. But the recent PLOS Biology paper by Knight and his colleagues is the first to suggest that scientists can eavesdrop on the brain to synthesize music. “These exciting findings build on previous work to reconstruct plain speech from brain activity,” says Shailee Jain, a neuroscientist at the University of California, San Francisco, who was not involved in the new study. “Now we’re able to really dig into the brain to unearth the sustenance of sound.” To turn brain activity data into musical sound in the study, the researchers trained an artificial intelligence model to decipher data captured from thousands of electrodes that were attached to the participants as they listened to the Pink Floyd song while undergoing surgery. Why did the team choose Pink Floyd—and specifically “Another Brick in the Wall (Part 1),”? “The scientific reason, which we mention in the paper, is that the song is very layered. It brings in complex chords, different instruments and diverse rhythms that make it interesting to analyze,” says Ludovic Bellier, a cognitive neuroscientist and the study’s lead author. “The less scientific reason might be that we just really like Pink Floyd.” Read the full article at: www.scientificamerican.com
Via Sara Mautino, Dr. Stefan Gruenwald
Terrible to terrific: A new antifungal molecule tweaks a powerful drug to harness its power against infection while doing away with its toxicity. A new antifungal molecule, devised by tweaking the structure of prominent antifungal drug Amphotericin B, has the potential to harness the drug’s power against fungal infections while doing away with its toxicity, researchers at the University of Illinois Urbana-Champaign and collaborators at the University of Wisconsin-Madison report in the journal Nature. Amphotericin B, a naturally occurring small molecule produced by bacteria, is a drug used as a last resort to treat fungal infections. While AmB excels at killing fungi, it is reserved as a last line of defense because it also is toxic to the human patient – particularly the kidneys. “Fungal infections are a public health crisis that is only getting worse. And they have the potential, unfortunately, of breaking out and having an exponential impact, kind of like COVID-19 did. So let’s take one of the powerful tools that nature developed to combat fungi and turn it into a powerful ally,” said research leader Dr. Martin D. Burke, an Illinois professor of chemistry, a professor in the Carle Illinois College of Medicine and also a medical doctor. “This work is a demonstration that, by going deep into the fundamental science, you can take a billion-year head start from nature and turn it into something that hopefully is going to have a big impact on human health,” Burke said. Burke’s group has spent years exploring AmB in hopes of making a derivative that can kill fungi without harm to humans. In previous studies, they developed and leveraged a building block-based approach to molecular synthesis and teamed up with a group specializing in molecular imaging tools called solid-state nuclear magnetic resonance, led by professor Chad Rienstra at the University of Wisconsin-Madison. Together, the teams uncovered the mechanism of the drug: AmB kills fungi by acting like a sponge to extract ergosterol from fungal cells. In the recent work, Burke’s group worked again with Rienstra’s group to find that AmB similarly kills human kidney cells by extracting cholesterol, the most common sterol in people. The researchers also resolved the atomic-level structure of AmB sponges when bound to both ergosterol and to cholesterol. “The atomic resolution models were really the key to zoom in and identify these very subtle differences in binding interactions between AmB and each of these sterols,” said Illinois graduate student Corinne Soutar, a co-first author of the paper. “Using this structural information along with functional and computational studies, we achieved a significant breakthrough in understanding how AmB functions as a potent fungicidal drug,” Rienstra said. “This provided the insights to modify AmB and tune its binding properties, reducing its interaction with cholesterol and thereby reducing the toxicity.” Read the full article at: news.illinois.edu
Via Dr. Stefan Gruenwald
The rise of Generative Artificial Intelligence has been nothing short of revolutionary, impacting every domain from finance to the arts. In the world of Read the full article at: petapixel.com
Google has been busy injecting AI-powered features into all of its services this year, and some of the most promising are in Google Maps. Well, this week those features – including the long-awaited Immersive View for Routes – are going to start rolling out on your Android or iOS phone, alongside some new tricks. The biggest news is the rollout of Immersive View for Routes in 15 cities, starting this week. The feature combines Street view, aerial imagery, and live information like weather and traffic to give you an aerial, photo-realistic preview of your planned Google Maps route – so we're excited to take it for a spin soon.
Read the full article at: www.techradar.com
Turn a radio telescope to the stars in the sky, and it's instantly deafened. From pulsars to radio galaxies, and ionospheric disturbances in the atmosphere to radio-frequency interference (RFI) from our own technology, the sky is a cacophony of radio noise. And somewhere, among all that, may lie a needle in a haystack: a signal from another world. For over 60 years scientists have been scanning the skies in the search for extraterrestrial life but have yet to find any aliens. When you consider the sheer volume of search space — all those stars, all those radio frequencies — versus our limited searches so far, then it's little wonder we've not found ET yet. It's a daunting task, especially for a human. Thankfully, we've got some non-human intelligence to join the search. The use of artificial intelligence (AI) is reaching critical mass, in our everyday lives and in science, so it is no surprise that it's now being employed in Search for Extraterrestrial Intelligence (SETI). AI is already helping astronomers make incredible discoveries. Here's how. We're not talking about Skynet, or the machines from The Matrix movies, or even Star Trek: The Next Generation's Data. The AI that is so in vogue at present is based on machine-learning algorithms designed to do very specific jobs, even if it's just to talk to you on ChatGPT. To explain how AI is assisting in SETI, astronomer and SETI researcher Eamonn Kerins of the University of Manchester compares it to the needle in a haystack problem. "You basically treat the data as though it's the hay," Kerins told Space.com Space.com. "Then you're asking the machine-learning algorithm to tell you if there is anything in the data that isn't hay, and that hopefully is the needle in the haystack — unless there's other stuff in the haystack too." That other stuff is usually RFI, but the machine-learning algorithm is trained to recognize all the types of RFI we already know about. Those signals — the familiar patterns of mobile phones, local radio transmitters, electronics and so on — are the hay. The training involves "injecting signals into the data and then the algorithm learns to look for signals that are like that," Steve Croft, an astronomer with the Breakthrough Listen SETI project at the University of California, Berkeley, told Space.com The algorithm learns to spot the patterns of these familiar signals and disregard them. Should it spot something in the data that it hasn't been trained on, then it flags this up as something interesting that requires a human to follow up on. "There have been attempts recently at sifting through some of the Breakthrough Listen data with a machine-learning algorithm," said Kerins. "The data had already been combed through quite carefully previously by more conventional means, but yet the algorithm was still able to pick out new signals after being trained on the stuff that we know about." This project was led by Croft and an undergraduate student, Peter Ma of the University of Toronto, who wrote the algorithm and put it to work analyzing data from 820 stars observed by the 100-meter radio telescope at Green Bank Observatory in West Virginia. The data, totaling 489 hours' worth of observations, contained millions of radio signals, almost all of which were human-made interference. The algorithm checked every single one of them and found eight signals that did not match anything it had been trained on and which had been missed by earlier analyses of the data. Read the full article at: www.space.com
Via Dr. Stefan Gruenwald
Genetic changes to avian influenza viruses have led to spread among many wild species, creating an uncontrollable global outbreak. Researchers studying the evolution of the bird flu virus over the past 18 years have shown how the strain currently circulating worldwide, an extremely deadly form of the H5N1 subtype, has become increasingly infectious to wild birds. The strain emerged in Europe in 2020, and has spread to an unprecedented number of countries. The study, published in Nature on the 18th October 2023 looked at changes to the virus’s genome over time and used data on reported outbreaks to track how it spread. In 2020, the rate of spread among wild birds was three times faster than that in farmed poultry, because of mutations that allowed the virus to adapt to diverse species. “What was once very clearly a poultry pathogen has now become an animal-health issue much more broadly,” says Andy Ramey, a wildlife geneticist at the US Geological Survey Alaska Science Center in Anchorage. “That has implications for wildlife and domestic poultry as well as us humans that rely upon these resources.”
Research Cited published in Nature (Oct. 18, 2023): https://doi.org/10.1038/s41586-023-06631-2
Read the full article at: www.nature.com
Via Juan Lama, Dr. Stefan Gruenwald
"Digital adoption platforms learn application usage patterns and user behaviors and walk workers through business processes in real time, offering guidance and automating tasks. They can help all of us get the most from AI ..." Read the full article at: www.infoworld.com
Via Leona Ungerer
Artificial intelligence takes a lot of compute power, and Microsoft is putting together a road map for powering that computation with small nuclear reactors. That’s according to a job description Microsoft posted Thursday seeking a nuclear technology expert to lead the company’s technical assessment for integrating small modular nuclear reactors and microreactors “to power the datacenters that the Microsoft Cloud and AI reside on,” the job posting reads. Specifically, Microsoft is looking to hire a “principal program manager for nuclear technology” and that person “will be responsible for maturing and implementing a global Small Modular Reactor (SMR) and microreactor energy strategy,” the job posting reads. Microsoft is looking to generate energy with nuclear fission, which is when an atom splits and releases energy as a result of that splitting. News of this job description was first reported on DCD, a website about data centers. In January 2023, Microsoft announced a multiyear, multibillion-dollar investment in OpenAI, maker of viral AI chatbot ChatGPT. Bill Gates, Microsoft’s co-founder, is also the chairman of the board of TerraPower, a nuclear innovation company in the process of developing and scaling small modular reactor designs. TerraPower “does not currently have any agreements to sell reactors to Microsoft,” a spokesperson told CNBC. However, Microsoft has publicly committed to pursuing nuclear energy from an innovator in the fusion space. In May, Microsoft announced it signed a power purchase agreement with Helion, a nuclear fusion startup, to buy electricity from it in 2028. Sam Altman, CEO of OpenAI, is an early and significant investor in Helion. Nuclear fusion occurs when two smaller atomic nuclei smash together to form a heavier atom and release tremendous quantities of energy in the process. It is the way in which the sun makes power. Fusion has not yet been recreated at scale here on earth, but many venture-backed startups are working to make it a reality due to the potential promise of virtually unlimited clean energy. Interest in nuclear energy has increased alongside concerns about climate change in recent years, as nuclear reactors generate electricity without releasing virtually any carbon dioxide emissions. The existing fleet of nuclear reactors in the U.S. was largely built between 1970 and 1990, and currently generates about 18% of the total electricity in the U.S., according to the U.S. Energy Information Administration. Nuclear energy also makes up 47% of America’s carbon-free electricity in 2022, according to the U.S. Department of Energy. Much of the hope for the next generation of nuclear reactor technology in the U.S. is pinned on smaller nuclear reactors, which Microsoft’s job posting indicates the company is interested in using to power its data centers. Read the full article at: www.cnbc.com
Via Dr. Stefan Gruenwald
The universe is humming with gravitational radiation—a very low-frequency rumble that rhythmically stretches and compresses spacetime and the matter embedded in it. That is the conclusion of several groups of researchers from around the world who simultaneously published a slew of journal articles in June describing more than 15 years of observations of millisecond pulsars within our corner of the Milky Way galaxy. At least one group—the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) collaboration—has found compelling evidence that the precise rhythms of these pulsars are affected by the stretching and squeezing of spacetime by these long-wavelength gravitational waves. "This is key evidence for gravitational waves at very low frequencies," says Vanderbilt University's Stephen Taylor, who co-led the search and is the current chair of the collaboration. "After years of work, NANOGrav is opening an entirely new window on the gravitational-wave universe."
Read the full article at: phys.org
Via Dr. Stefan Gruenwald
A new study highlights both the promise and the limitations of gene editing, as a highly lethal form of avian influenza continues to spread around the world. Scientists have used the gene-editing technology known as CRISPR to create chickens that have some resistance to avian influenza, according to a new study that was published in the journal Nature Communications on Tuesday. The study suggests that genetic engineering could potentially be one tool for reducing the toll of bird flu, a group of viruses that pose grave dangers to both animals and humans. But the study also highlights the limitations and potential risks of the approach, scientists said. Some breakthrough infections still occurred, especially when gene-edited chickens were exposed to very high doses of the virus, the researchers found. And when the scientists edited just one chicken gene, the virus quickly adapted. The findings suggest that creating flu-resistant chickens will require editing multiple genes and that scientists will need to proceed carefully to avoid driving further evolution of the virus, the study’s authors said. The research is “proof of concept that we can move toward making chickens resistant to the virus,” Wendy Barclay, a virologist at Imperial College London and an author of the study, said at a news briefing. “But we’re not there yet.” Some scientists who were not involved in the research had a different takeaway. “It’s an excellent study,” said Dr. Carol Cardona, an expert on bird flu and avian health at the University of Minnesota. But to Dr. Cardona, the results illustrate how difficult it will be to engineer a chicken that can stay a step ahead of the flu, a virus known for its ability to evolve swiftly. “There’s no such thing as an easy button for influenza,” Dr. Cardona said. “It replicates quickly, and it adapts quickly.” What to Know About Avian FluThe spread of H5N1. A new variant of this strain of the avian flu has spread widely through bird populations in recent years. It has taken an unusually heavy toll on wild birds and repeatedly spilled over into mammals, including minks, foxes and bears.
Read the full article at: www.nytimes.com
Via Juan Lama, Dr. Stefan Gruenwald
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AI's remarkable abilities, like those seen in ChatGPT, often seem conscious due to their human-like interactions. The question is whether the language model also perceives our text when we prompt it. Or is it just a zombie, working based on clever pattern-matching algorithms? Based on the text it generates, it is easy to be swayed that the system might be conscious. However, in this new research, Jaan Aru, Matthew Larkum and Mac Shine take a neuroscientific angle to answer this question. All three being neuroscientists, these authors argue that although the responses of systems like ChatGPT seem conscious, they are most likely not. First, the inputs to language models lack the embodied, embedded information content characteristic of our sensory contact with the world around us. Secondly, the architectures of present-day AI algorithms are missing key features of the thalamocortical system that have been linked to conscious awareness in mammals. Finally, the evolutionary and developmental trajectories that led to the emergence of living conscious organisms arguably have no parallels in artificial systems as envisioned today. The existence of living organisms depends on their actions and their survival is intricately linked to multi-level cellular, inter-cellular, and organismal processes culminating in agency and consciousness. Thus, while it is tempting to assume that ChatGPT and similar systems might be conscious, this would severely underestimate the complexity of the neural mechanisms that generate consciousness in our brains. Researchers do not have a consensus on how consciousness rises in our brains. What we know, and what this new paper points out, is that the mechanisms are likely way more complex than the mechanisms underlying current language models. For instance, as pointed out in this work, real neurons are not akin neurons in artificial neural networks. Biological neurons are real physical entities, which can grow and change shape, whereas neurons in large language models are just meaningless pieces of code. We still have a long way to understand consciousness and, hence, a long way to conscious machines. Read the full article at: neurosciencenews.com
Via Enzo Calamo, Dr. Stefan Gruenwald
Scientists found the cells in mice — and say they could lead to a better understanding of human appetite. Brain cells that control how quickly mice eat, and when they stop, have been identified. The findings, published in Nature1, could lead to a better understanding of human appetite, the researchers say. Nerves in the gut, called vagal nerves, had already been shown to sense how much mice have eaten and what nutrients they have consumed2. The vagal nerves use electrical signals to pass this information to a small region in the brainstem that is thought to influence when mice, and humans, stop eating. This region, called the caudal nucleus of the solitary tract, contains prolactin-releasing hormone neurons (PRLH) and GCG neurons. But, until now, studies have involved filling the guts of anaesthetized mice with liquid food, making it unclear how these neurons regulate appetite when mice are awake. To answer this question, physiologist Zachary Knight at the University of California, San Francisco, and his colleagues implanted a light sensor in the brains of mice that had been genetically modified so that the PRLH neurons released a fluorescent signal when activated by electrical signals transmitted along neurons from elsewhere in the body. Knight and his team infused a liquid food called Ensure — which contains a mixture of fat, protein, sugar, vitamins and minerals — into the guts of these mice. Over a ten-minute period, the neurons became increasingly activated as more of the food was infused. This activity peaked a few minutes after the infusion ended. By contrast, the PRLH neurons did not activate when the team infused saline solution into the mice’s guts. When the team allowed the mice to freely eat liquid food, the PRLH neurons activated within seconds of the animals starting to lick the food, but deactivated when they stopped licking. This showed that PRLH neurons respond differently, depending on whether signals are coming from the mouth or the gut, and suggests that signals from the mouth override those from the gut, says Knight. By using a laser to activate PRLH neurons in mice that were eating freely, the researchers could reduce how quickly the mice ate. Further experiments showed that PRLH neurons did not activate during feeding in mice that lacked most of their ability to taste sweetness, suggesting that taste activated the neurons. The researchers also found that GCG neurons are activated by signals from the gut, and control when mice stop eating. “The signals from the mouth are controlling how fast you eat, and the signals from the gut are controlling how much you eat,” says Knight. “I’m extremely impressed by this paper,” says neuroscientist Chen Ran at Harvard University in Boston, Massachusetts. The work provides original insights on how taste regulates appetite, he says. The findings probably apply to humans, too, Ran adds, because these neural circuits tend to be well conserved across both species. Read the full article at: www.nature.com
Via Dr. Stefan Gruenwald
Scientists are training a gargantuan one-trillion-parameter generative AI system dubbed 'ScienceGPT' based on scientific data from the newly established Aurora supercomputer. The AuroraGPT AI model, which is being trained by researchers at the Argonne National Lab (ALN) in Illinois, USA, is powered by Intel's Ponte Vecchio GPUs which provide the main computing power, and is being backed by the US government. Training could take months to complete, according to HPC Wire, with training currently limited to 256 of the roughly 10,000 nodes of the Aurora supercomputer, before this is scaled up over time. Even given this limitation, Intel and ANL are only testing the model training on a string of 64 nodes, with caution due to Aurora's unique design as a supercomputer. At one trillion parameters, ScienceGPT will be one of the largest LLMs out there. While it won't quite hit the size of the reported 1.7-trillion-parameter GPT-4, developed by OpenAI, it'll be almost twice as large as the 560-billion-parameter Pathways Language Model, which powers Google's Bard. “It combines all the text, codes, specific scientific results, papers, into the model that science can use to speed up research,” said Ogi Brkic, vice president and general manager for data center and HPC solutions, in a press briefing. It'll operate like ChatGPT, but it's yet unclear at the moment whether it will be multimodal, in that it will generate different kinds of media like text, images, and video. Aurora – which will be the second exascale supercomputer in US history – has just established itself on the Top500 list of the most powerful supercomputers after years of being developed. It's the second-most powerful supercomputer after Froniter, and is powered by 60,000 Intel GPUs while boating 10,000 computing nodes over 166 racks, alongside more than 80,000 networking nodes. It is still being finished, however, and will likely exceed Frontier's performance when it's fully up to speed, and all testing and finetuning is complete, said Top500. Read the full article at: www.techradar.com
Via Dr. Stefan Gruenwald
Deep within every piece of magnetic material, electrons dance to the invisible tune of quantum mechanics. Their spins, akin to tiny atomic tops, dictate the magnetic behavior of the material they inhabit. This microscopic ballet is the cornerstone of magnetic phenomena, and it's these spins that a team of JILA researchers—headed by JILA Fellows and University of Colorado Boulder professors Margaret Murnane and Henry Kapteyn—has learned to control with remarkable precision, potentially redefining the future of electronics and data storage. In a Science Advances publication, the JILA team—along with collaborators from universities in Sweden, Greece, and Germany—probed the spin dynamics within a special material known as a Heusler compound: a mixture of metals that behaves like a single magnetic material. For this study, the researchers utilized a compound of cobalt, manganese, and gallium, which behaved as a conductor for electrons whose spins were aligned upwards and as an insulator for electrons whose spins were aligned downwards. Using a form of light called extreme ultraviolet high-harmonic generation (EUV HHG) as a probe, the researchers could track the re-orientations of the spins inside the compound after exciting it with a femtosecond laser, which caused the sample to change its magnetic properties. The key to accurately interpreting the spin re-orientations was the ability to tune the color of the EUV HHG probe light. "In the past, people haven't done this color tuning of HHG," explained co-first author and JILA graduate student Sinéad Ryan. "Usually, scientists only measured the signal at a few different colors, maybe one or two per magnetic element at most." In a monumental first, the JILA team tuned their EUV HHG light probe across the magnetic resonances of each element within the compound to track the spin changes with a precision down to femtoseconds (a quadrillionth of a second). "On top of that, we also changed the laser excitation fluence, so we were changing how much power we used to manipulate the spins," Ryan elaborated, highlighting that that step was also an experimental first for this type of research. Read the full article at: phys.org
Via Dr. Stefan Gruenwald
If our eyes could see high-energy radiation called gamma rays, the Moon would appear brighter than the Sun! That’s how NASA’s Fermi Gamma-ray Space Telescope has seen our neighbor in space for the past decade. Gamma-ray observations are not sensitive enough to clearly see the shape of the Moon’s disk or any surface features. Instead, Fermi’s Large Area Telescope (LAT) detects a prominent glow centered on the Moon’s position in the sky. Mario Nicola Mazziotta and Francesco Loparco, both at Italy’s National Institute of Nuclear Physics in Bari, have been analyzing the Moon’s gamma-ray glow as a way of better understanding another type of radiation from space: fast-moving particles called cosmic rays. “Cosmic rays are mostly protons accelerated by some of the most energetic phenomena in the universe, like the blast waves of exploding stars and jets produced when matter falls into black holes,” explained Mazziotta. Because the particles are electrically charged, they’re strongly affected by magnetic fields, which the Moon lacks. As a result, even low-energy cosmic rays can reach the surface, turning the Moon into a handy space-based particle detector. When cosmic rays strike, they interact with the powdery surface of the Moon, called the regolith, to produce gamma-ray emission. The Moon absorbs most of these gamma rays, but some of them escape. Mazziotta and Loparco analyzed Fermi LAT lunar observations to show how the view has improved during the mission. They rounded up data for gamma rays with energies above 31 million electron volts — more than 10 million times greater than the energy of visible light — and organized them over time, showing how longer exposures improve the view. “Seen at these energies, the Moon would never go through its monthly cycle of phases and would always look full,” said Loparco. As NASA sets its sights on sending humans to the Moon by 2024 through the Artemis program, with the eventual goal of sending astronauts to Mars, understanding various aspects of the lunar environment take on new importance. These gamma-ray observations are a reminder that astronauts on the Moon will require protection from the same cosmic rays that produce this high-energy gamma radiation. While the Moon’s gamma-ray glow is surprising and impressive, the Sun does shine brighter in gamma rays with energies higher than 1 billion electron volts. Cosmic rays with lower energies do not reach the Sun because its powerful magnetic field screens them out. But much more energetic cosmic rays can penetrate this magnetic shield and strike the Sun’s denser atmosphere, producing gamma rays that can reach Fermi. Although the gamma-ray Moon doesn’t show a monthly cycle of phases, its brightness does change over time. Fermi LAT data show that the Moon’s brightness varies by about 20% over the Sun’s 11-year activity cycle. Variations in the intensity of the Sun’s magnetic field during the cycle change the rate of cosmic rays reaching the Moon, altering the production of gamma rays. Download the graphic and related multimedia in HD formats from NASA Goddard’s Scientific Visualization Studio Read the full article at: www.nasa.gov
Via Dr. Stefan Gruenwald
No one had ever seen one virus latching onto another virus, until anomalous sequencing results sent a UMBC team down a rabbit hole leading to a first-of-its-kind discovery. It's known that some viruses, called satellites, depend not only on their host organism to complete their life cycle, but also on another virus, known as a "helper," explains Ivan Erill, professor of biological sciences. The satellite virus needs the helper either to build its capsid, a protective shell that encloses the virus's genetic material, or to help it replicate its DNA. These viral relationships require the satellite and the helper to be in proximity to each other at least temporarily, but there were no known cases of a satellite actually attaching itself to a helper—until now. In a paper published in The ISME Journal, a UMBC team and colleagues from Washington University in St. Louis (WashU) describe the first observation of a satellite bacteriophage (a virus that infects bacterial cells) consistently attaching to a helper bacteriophage at its "neck"—where the capsid joins the tail of the virus. In detailed electron microscopy images taken by Tagide deCarvalho, assistant director of the College of Natural and Mathematical Sciences Core Facilities and first author on the new paper, 80 percent (40 out of 50) helpers had a satellite bound at the neck. Some of those that did not had remnant satellite tendrils present at the neck. Erill, senior author on the paper, describes them as appearing like "bite marks." "When I saw it, I was like, I can't believe this," deCarvalho says. "No one has ever seen a bacteriophage—or any other virus—attach to another virus."
Research is published in ISME (October 31, 2023): https://doi.org/10.1038/s41396-023-01548-0
Read the full article at: phys.org
Via Juan Lama, Dr. Stefan Gruenwald
Some employers are either tacitly or outright banning access to generative AI tools like ChatGPT. But employees who love them are finding ways to discreetly backchannel. Read the full article at: www.bbc.com
A study of a lizard species in Arizona revealed that nearly 70 years' worth of climate-related extinction occurred in just seven years. Researchers surveyed populations of the Yarrow’s spiny lizard in 18 mountain ranges in southeastern Arizona and analyzed the rate of climate-related extinction over time. “The magnitude of extinction we found over the past seven years was similar to that seen in other studies that spanned almost 70 years,” says John J. Wiens, a professor in the ecology and evolutionary biology department at the University of Arizona and senior author of the study in Ecology Letters. The Yarrow’s spiny lizard native to the southwestern US and western Mexico can be spotted in oak and pine forests in 18 of Arizona’s Sky Islands mountain ranges. Wiens and his group did initial surveys of the Yarrow’s spiny lizard in these mountain ranges in 2014 and 2015. In 2021 and 2022, Wiens, along with Kim Holzmann, his former master’s student and the new study’s lead author, and Ramona Walls, a part-time researcher at the University of Arizona’s BIO5 institute, resurveyed to investigate if there had been any changes in the lizard populations since then. They found that about half of the lizard populations at lower elevations had disappeared. This is because temperatures are warmer at lower elevations, Wiens says, and the lizards at lower elevations were presumably not able to tolerate the increasing heat. This loss of low-elevation populations is a signature pattern of climate change, he says. “The rate of extinction in such a short time period was shocking,” Wiens says. After comparing the findings to historical records from the same mountain ranges, Wiens’ group found that the average extinction rate of the lizard populations at low elevations had tripled over the past seven years, relative to the preceding 42 years. Although previous studies have predicted that climate-related extinctions will increase with the rising pace of global warming, Wiens says he hasn’t seen any showing that this acceleration of extinction has already happened. Also, a distinct 3-million-year-old lineage of the Yarrow’s spiny lizard from the Mule Mountains, near Bisbee, may be completely extinct by 2025, Wiens says. “The low-elevation populations in the Mules were fine in 2014. Now the only ones that we have found left were within about 300 feet of the top of the mountain in 2022, and they appear to have been losing about 170 feet per year,” he says. However, not all low-elevation populations went extinct between the surveys, Wiens says. For example, two populations that occurred at very low elevations survived. Before they disappeared, the research group had collected genomic data from most of those populations in 2014 and 2015. They found that those populations that were less genetically variable and were exposed to greater climate change effects were the ones that tended to go extinct. This suggests that the populations with less genetic variation had less ability to adapt to climate change. Read the full article at: www.futurity.org
Via Ed Rybicki, Dr. Stefan Gruenwald
Initial studies of the 4.5-billion-year-old asteroid Bennu sample collected in space and brought to Earth by NASA show evidence of high-carbon content and water, which together could indicate the building blocks of life on Earth may be found in the rock. NASA made the news Wednesday from its Johnson Space Center in Houston where leadership and scientists showed off the asteroid material for the first time since it landed in September. This finding was part of a preliminary assessment of NASA’s OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification and Security – Regolith Explorer) science team. “The OSIRIS-REx sample is the biggest carbon-rich asteroid sample ever delivered to Earth and will help scientists investigate the origins of life on our own planet for generations to come,” said NASA Administrator Bill Nelson. “Almost everything we do at NASA seeks to answer questions about who we are and where we come from. NASA missions like OSIRIS-REx will improve our understanding of asteroids that could threaten Earth while giving us a glimpse into what lies beyond. The sample has made it back to Earth, but there is still so much science to come – science like we’ve never seen before.” Although more work is needed to understand the nature of the carbon compounds found, the initial discovery bodes well for future analyses of the asteroid sample. The secrets held within the rocks and dust from the asteroid will be studied for decades to come, offering insights into how our solar system was formed, how the precursor materials to life may have been seeded on Earth, and what precautions need to be taken to avoid asteroid collisions with our home planet.
Read the full article at: www.nasa.gov
Via Dr. Stefan Gruenwald
Researchers at North Carolina State University and global collaborators have mapped the mosquito's tree of life, a major step toward understanding important traits, such as how the insects choose their hosts, feed on blood and spread disease. The findings will help researchers make better predictions to model disease transmission and understand what makes some mosquitoes better disease carriers than others. The research suggests that mosquito evolution over the past 200 million years mirrors the Earth's history of shifting land masses and changing host organisms, says Dr. Brian Wiegmann, William Neal Reynolds Professor of Entomology at NC State and corresponding author of a paper describing the mosquito family tree, published in Nature Communications.
Read the full article at: phys.org
Via Dr. Stefan Gruenwald
Adobe Illustrator is a widely used vector graphics tool for graphic artists and it’s about to join the generative AI era with the launch of the Firefly Vector Model at Adobe’s MAX conference today. Adobe describes the new model as “the world’s first generative AI model focused on producing vector graphics.” Like Firefly for creating images and photos, Firefly for Illustrator will be able to create entire vector graphics from scratch. And like the other Firefly models, the vector model, too, was trained on data from Adobe Stock. In its beta, Illustrator will now let you create entire scenes through a text prompt. What’s nifty here is that those scenes can consist of multiple objects. So this isn’t just a jumble of vectors that make up the overall graphic but Illustrator will automatically generate these different objects and you can manipulate them individually to your heart’s content, just like any other group or layer in Illustrator. Alexandru Costin, Adobe’s VP for generative AI and Sensei, told me the company used tens of millions of vector images in Adobe Stock to train Firefly to enable this new capability. Costin described the process as “a journey” and since there hasn’t been as much work done on using generative AI to create vector drawings compared to the work on creating other images, this surely took a bit more work on the team’s part. He noted that the team focused on creating a model that could generate these images with the fewest possible points, too. Another new feature that’s coming to Illustrator is called Mockup, which allows Illustrator users to take any 3D scene and then take any vector art and apply it to that 3D scene. That could be a design for a drink can, for example, or a mockup of a new logo on a t-shirt. “Mockup is really exciting to show your customers the art in context so they understand what they’re buying when they contract you as a freelancer,” Costin explained. Also new is Retype, which converts static text in images to editable text — and it’ll find matching fonts, too — and Illustrator is now available on the web, too! Read the full article at: techcrunch.com
Via Dr. Stefan Gruenwald
New research indicates that severe space weather events, such as solar flares, disrupt birds' navigational skills during long migrations. Previous research has indicated that when flying at night, birds (and many other animals) use Earth's magnetic field for navigation. Because solar events disrupt the magnetic field — as well as produce auroras — birds have more difficulty navigating during them. The new study analyzed images taken from 37 NEXRAD Doppler weather radar stations, which can detect groups of migrating birds, as well as data from ground-based magnetometers, to study 23 years of bird migration across the U.S. Great Plains. The 1,000-mile (1,600-kilometer) span from North Dakota to Texas is considered a major migratory corridor for birds. "The biggest challenge was trying to distill such a large dataset — years and years of ground magnetic field observations — into a geomagnetic disturbance index for each radar site," Daniel Welling, University of Michigan space scientist said in a statement. "There was a lot of heavy lifting in terms of assessing data quality and validating our final data product to ensure that it was appropriate for this study." The work paid off. The researchers discovered that the number of migrating birds in this region decreases by 9 to 17 percent during severe space weather events. They also noticed increased rates of birds becoming lost during migration, a phenomenon known as migratory bird vagrancy. Read the full article at: www.space.com
Via Dr. Stefan Gruenwald
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