We've just had the world's first press conference with AI-enabled, humanoid social robots. Click here to jump straight to Slashdot's transcript of all the robots' answers during the press conference, or watch the 40-minute video here.

It all happened as the United Nations held an "AI for Good" summit in Geneva, where the Guardian reports that the foyer was "humming with robotic voices, the whirring of automated wheels and limbs, and Desdemona, the 'rock star' humanoid, who is chanting 'the singularity will not be centralised' on stage backed by a human band, Jam Galaxy."

But the Associated Press describes how one UN agency had "assembled a group of robots that physically resembled humans at a news conference Friday, inviting reporters to ask them questions in an event meant to spark discussion about the future of artificial intelligence. "The nine robots were seated and posed upright along with some of the people who helped make them at a podium in a Geneva conference center... Among them: Sophia, the first robot innovation ambassador for the U.N. Development Program, or UNDP; Grace, described as a health care robot; and Desdemona, a rock star robot."

"I'm terrified by all of this," said one local newscaster, noting that the robots also said they "had no intention of rebelling against their creators."

But the Associated Press points out an important caveat: While the robots vocalized strong statements - that robots could be more efficient leaders than humans, but wouldn't take anyone's job away or stage a rebellion - organizers didn't specify to what extent the answers were scripted or programmed by people. The summit was meant to showcase "human-machine collaboration," and some of the robots are capable of producing preprogrammed responses, according to their documentation.
Two of the robots seemed to disagree on whether AI-powered robots should submit to stricter regulation. (Although since they're only synthesizing sentences from large-language models, can they really be said to "agree" or "disagree"?)

There were unintentionally humorous moments, starting right from the beginning. Click here to start reading Slashdot's transcript of the robots' answers:

An anonymous reader quotes a report from Ars Technica: The Brave browser will take action against websites that snoop on visitors by scanning their open Internet ports or accessing other network resources that can expose personal information. Starting in version 1.54, Brave will automatically block website port scanning, a practice that a surprisingly large number of sites were found engaging in a few years ago. According to this list compiled in 2021 by a researcher who goes by the handle G666g1e, 744 websites scanned visitors' ports, most or all without providing notice or seeking permission in advance. eBay, Chick-fil-A, Best Buy, Kroger, and Macy's were among the offending websites.

Some sites use similar tactics in an attempt to fingerprint visitors so they can be re-identified each time they return, even if they delete browser cookies. By running scripts that access local resources on the visiting devices, the sites can detect unique patterns in a visiting browser. Sometimes there are benign reasons a site will access local resources, such as detecting insecurities or allowing developers to test their websites. Often, however, there are more abusive or malicious motives involved.

The new version of Brave will curb the practice. By default, no website will be able to access local resources. More advanced users who want a particular site to have such access can add it to an allow list. The interface will look something like the screenshot displayed [here]. Brave will continue to use filter list rules to block scripts and sites known to abuse localhost resources. Additionally, the browser will include an allow list that gives the green light to sites known to access localhost resources for user-benefiting reasons. "Brave has chosen to implement the localhost permission in this multistep way for several reasons," developers of the browser wrote. "Most importantly, we expect that abuse of localhost resources is far more common than user-benefiting cases, and we want to avoid presenting users with permission dialogs for requests we expect will only cause harm."

"As far as we can tell, Brave is the only browser that will block requests to localhost resources from both secure and insecure public sites, while still maintaining a compatibility path for sites that users trust (in the form of the discussed localhost permission)" the Brave post said.

An anonymous reader quotes a report from Reuters: When former Samsung executive Choi Jinseog won a contract with Taiwan's Foxconn in 2018, he tapped his former employer's supplier network to steal secrets to help his new client set up a chip factory in China, a sealed indictment by South Korean prosecutors alleges. Prosecutors announced the indictment on June 12, saying the theft caused more than $200 million in damages to Samsung Electronics, based on the estimated costs Samsung spent to develop the stolen data. The announcement did not name Choi and gave only limited details, although some media subsequently identified Choi and his links with Foxconn. The unreleased 18-page indictment, reviewed by Reuters, provides details in the case against Choi, including how he is alleged to have stolen Samsung's trade secrets and details about the planned Foxconn plant.

Choi, who has been detained in jail since late May, denied all the charges through his lawyer, Kim Pilsung. Choi's Singapore-based consultancy Jin Semiconductor won the contract with Foxconn around August 2018, according to the indictment. Within months, Choi had poached "a large number" of employees from Samsung and its affiliates and illegally obtained secret information related to building a chip factory from two contractors, prosecutors allege. Jin Semiconductor illegally used confidential information involving semiconductor cleanroom management obtained from Cho Young-sik who worked at one of the contractors, Samoo Architects & Engineers, the indictment alleges. Clean rooms are manufacturing facilities where the enclosed environment is engineered to remove dust and other particles that can damage highly sensitive chips. Samoo had participated in the 2012 construction of Samsung's chip plant in Xian, China. Prosecutors allege Choi's company also illegally obtained blueprints of Samsung's China plant from Chung Chan-yup, an employee at HanmiGlobal, which supervised its construction and floor layouts involving the chip manufacturing process. They have yet to establish how the information on floor layout was obtained, according to the indictment.

Choi signed a preliminary consulting contract in around 2018 with Foxconn to build the chip factory potentially in Xian, his lawyer said. However, Foxconn ended the contract just a year later and only paid salaries related to the project, the lawyer said. He declined to comment on why Foxconn ended the contract or to provide further details, citing the sensitivity of the matter. The person with direct knowledge of the case said prosecutors found Foxconn had agreed to provide 8 trillion won ($6 billion) to build the factory, and Foxconn also paid several million dollars to Choi's company every month until it pulled out of the contract for reasons the indictment did not disclose. Jin Semiconductor's financial statement in 2018 said it entered into an arrangement with "a major customer" for the provision of qualified manpower in the next five years. The customer paid an advance of $17,994,217 to the company, according to the statement. Choi's lawyer said his client may be a scapegoat in a campaign by the South Korean government, caught in a rivalry between China and the United States, seeking seek to slow China's progress in chip manufacturing. [...] Choi is charged along with five other former and current Jin Semiconductor employees and a Samsung contractor employee. Trial is set to begin on July 12, court records show.

Today, Rivian announced that it is switching from the Combined Charging System (CCS) standard to the North American Charging Standard (NACS), tesla's competing standard, in 2024. The automaker joins Ford and General Motors in adopting Tesla's charging plugs for its future electric vehicles. Ars Technica reports: "We're excited to work with Tesla and to see collaborations like this help advance the world toward carbon neutrality. The adoption of the North American Charging Standard will enable our existing and future customers to leverage Tesla's expansive Supercharger network while we continue to build out our Rivian Adventure Network. We look forward to continuing to find new ways to accelerate EV adoption," said Rivian founder and CEO RJ Scaringe in a statement.

In an email to customers, Rivian said that it would make adapters available, so people should not wait for the factory to switch over to the NACS port from CCS1. It also says that it will add Tesla charging sites to its mobile and vehicle navigation apps. From 2025, it will start building NACS ports into its vehicles. Like GM, Rivian is in the midst of deploying thousands of DC fast chargers with CCS1 plugs, and like GM, Rivian says that the switch to NACS does not affect those plans. As with Ford and GM, there are no details as to the terms of the deal between Rivian and Tesla.

An anonymous reader quotes a report from The Guardian: Scientists have created synthetic human embryos using stem cells, in a groundbreaking advance that sidesteps the need for eggs or sperm. Scientists say these model embryos, which resemble those in the earliest stages of human development, could provide a crucial window on the impact of genetic disorders and the biological causes of recurrent miscarriage. However, the work also raises serious ethical and legal issues as the lab-grown entities fall outside current legislation in the UK and most other countries. The structures do not have a beating heart or the beginnings of a brain, but include cells that would typically go on to form the placenta, yolk sac and the embryo itself.

There is no near-term prospect of the synthetic embryos being used clinically. It would be illegal to implant them into a patient's womb, and it is not yet clear whether these structures have the potential to continue maturing beyond the earliest stages of development. The motivation for the work is for scientists to understand the "black box" period of development that is so called because scientists are only allowed to cultivate embryos in the lab up to a legal limit of 14 days. They then pick up the course of development much further along by looking at pregnancy scans and embryos donated for research. The full details of the latest work, from the Cambridge-Caltech lab, are yet to be published in a journal paper. But, speaking at the conference, Zernicka-Goetz described cultivating the embryos to a stage just beyond the equivalent of 14 days of development for a natural embryo.

The model structures, each grown from a single embryonic stem cell, reached the beginning of a developmental milestone known as gastrulation, when the embryo transforms from being a continuous sheet of cells to forming distinct cell lines and setting up the basic axes of the body. At this stage, the embryo does not yet have a beating heart, gut or beginnings of a brain, but the model showed the presence of primordial cells that are the precursor cells of egg and sperm. "Our human model is the first three-lineage human embryo model that specifies amnion and germ cells, precursor cells of egg and sperm," Zernicka-Goetz told the Guardian before the talk. "It's beautiful and created entirely from embryonic stem cells."

Because of their intrinsic ability to consider many possibilities at once, quantum computers do not have to be very large to tackle certain prickly problems of computation, and on Wednesday, IBM researchers announced that they had devised a method to manage the unreliability in a way that would lead to reliable, useful answers. From a report: "What IBM showed here is really an amazingly important step in that direction of making progress towards serious quantum algorithmic design," said Dorit Aharonov, a professor of computer science at the Hebrew University of Jerusalem who was not involved with the research. While researchers at Google in 2019 claimed that they had achieved "quantum supremacy" -- a task performed much more quickly on a quantum computer than a conventional one -- IBM's researchers say they have achieved something new and more useful, albeit more modestly named. "We're entering this phase of quantum computing that I call utility," said Jay Gambetta, a vice president of IBM Quantum. "The era of utility." A team of IBM scientists who work for Dr. Gambetta described their results in a paper published on Wednesday in the journal Nature.

[...] The IBM researchers in the new study performed a different task, one that interests physicists. They used a quantum processor with 127 qubits to simulate the behavior of 127 atom-scale bar magnets -- tiny enough to be governed by the spooky rules of quantum mechanics -- in a magnetic field. That is a simple system known as the Ising model, which is often used to study magnetism. This problem is too complex for a precise answer to be calculated even on the largest, fastest supercomputers. On the quantum computer, the calculation took less than a thousandth of a second to complete. Each quantum calculation was unreliable -- fluctuations of quantum noise inevitably intrude and induce errors -- but each calculation was quick, so it could be performed repeatedly.

This week the Linux Foundation announced the publication of The Open Source Opportunity for Microgrids: Five Ways to Drive Innovation and Overcome Market Barriers for Energy Resilience. "The research informs readers about microgrids — groups of distributed energy resources designed to improve energy resiliency, with the ability to operate as part of a larger electrical grid, or separately as an island."

The report highlights the current state of the microgrid market and explores the potential for open source technology to accelerate the adoption of microgrids worldwide... The report concludes that microgrids are an essential tool to improve energy resilience and advance decarbonization, and that the market faces a range of challenges that the open source ecosystem is well positioned to address.
Among other things, the report "examines how participation in relevant open source programs and activities can help address gaps and challenges," according to the announcement, "and accelerate the learning, development, and governance of microgrid initiatives." One focus of the report is "enabling market innovation toward energy resilience at scale, supporting the Energy sector to adopt proven open source-enabled business models, security benefits, and cost reductions demonstrated in the IT and Telecom industries."

And according to the foundation's senior vice president of research and communications, the report also "describes the opportunities for open source to accelerate the proliferation of microgrids as a mechanism for clean energy production and consumption."

Biden administration officials are divided over how aggressively new artificial intelligence tools should be regulated -- and their differences are playing out this week in Sweden. From a report: Some White House and Commerce Department officials support the strong measures proposed by the European Union for AI products such as ChatGPT and Dall-E, people involved in the discussions said. Meanwhile, US national security officials and some in the State Department say aggressively regulating this nascent technology will put the nation at a competitive disadvantage, according to the people, who asked not to be identified because the information isn't public. This dissonance has left the US without a coherent response during this week's US-EU Trade and Technology Council gathering in Sweden to the EU's plan to subject generative AI to additional rules. The proposal would force developers of artificial intelligence tools to comply with a host of strong regulations, such as requiring them to document any copyrighted material used to train their products and more closely track how that information is used. National Security Council spokesman Adam Hodge said the Biden administration is working across the government to "advance a cohesive and comprehensive approach to AI-related risks and opportunities."

Last month Japanese startup ispace tried to become the first private company to land a spacecraft on the moon — but in the crucial final moments lost contact with its vehicle.

Now the Associated Press reports that company officials are revealing what happened: while trying to land, their vehicle went into free-fall. Company officials blame a software issue, plus a decision in December to change the touchdown location to a crater. The crater's steep sides apparently confused the onboard software, and the 7-foot (2-meter) spacecraft went into a free-fall from less than 3 miles (5 kilometers) up, slamming into the lunar surface. The estimated speed at impact was more than 300 feet (100 meters) per second, said the company's chief technology officer, Ryo Ujiie.

NASA's Lunar Reconnaissance Orbiter photographed the crash site the next day as it flew overhead, revealing a field of debris as well as lunar soil hurled aside by the impact. Computer simulations done in advance of the landing attempt did not incorporate the terrain of the new landing site, Ujiie said.

CEO and founder Takeshi Hakamada said the company is still on track to attempt another moon landing in 2024, and that all the lessons learned will be incorporated into the next try. A third landing attempt is planned for 2025.

The two Koreas are elevating a space race aimed at modernizing how each country monitors the other's improving military firepower. From a report: As hopes for a diplomatic breakthrough have dimmed in recent years, North and South Korea have grown more antagonistic toward one another and upped their displays of military might. They have traded missile tests. Pyongyang has sent drones that flew over downtown Seoul. South Korea has sharpened security and defense ties with the U.S. and Japan. The rise in tensions has elevated the importance -- and need -- for spy-satellite technology that neither country now has. South Korea cleared a significant technological marker on Thursday, launching multiple commercial satellites aboard a homegrown rocket for the first time. North Korea's Kim Jong Un regime stands poised to soon fly its first military reconnaissance satellite.

Nuri, South Korea's three-stage liquid-fuel rocket, blasted off at 6:24 p.m. local time Thursday from the Naro Space Center in Goheung, a city on the country's southern coast. The 200-ton rocket launched into space and deployed eight satellites into orbit about 342 miles above Earth, about 13 minutes after liftoff. Seoul has the clear technological advantage, weapons analysts say, though Pyongyang has been quick to advance its sanctioned missile program to develop long-range rockets that can carry satellites. Both nations remain years away from having a full-fledged network of spy satellites. But attaining the technology would allow the countries to identify military targets to precisely launch strikes during potential conflict without relying on their allies' satellite technology for information. In North Korea's case, space-based satellite technology is essential for its nuclear strategy. Having eyes in the sky would serve as an additional asset to launching nuclear strikes with better accuracy, said Yang Uk, a military expert at the Asan Institute for Policy Studies, a think tank in Seoul. Should the technology progress enough, North Korea could potentially identify nuclear strike targets in the U.S., he added.

Sundar Pichai, CEO of Google and Alphabet, writing at Financial Times: While some have tried to reduce this moment to just a competitive AI race, we see it as so much more than that. At Google, we've been bringing AI into our products and services for over a decade and making them available to our users. We care deeply about this. Yet, what matters even more is the race to build AI responsibly and make sure that as a society we get it right. We're approaching this in three ways. First, by boldly pursuing innovations to make AI more helpful to everyone. We're continuing to use AI to significantly improve our products -- from Google Search and Gmail to Android and Maps. These advances mean that drivers across Europe can now find more fuel-efficient routes; tens of thousands of Ukrainian refugees are helped to communicate in their new homes; flood forecasting tools are able to predict floods further in advance. Google DeepMind's work on AlphaFold, in collaboration with the European Molecular Biology Laboratory, resulted in a groundbreaking understanding of over 200mn catalogued proteins known to science, opening up new healthcare possibilities.

Our focus is also on enabling others outside of our company to innovate with AI, whether through our cloud offerings and APIs, or with new initiatives like the Google for Startups Growth program, which supports European entrepreneurs using AI to benefit people's health and wellbeing. We're launching a social innovation fund on AI to help social enterprises solve some of Europe's most pressing challenges. Second, we are making sure we develop and deploy the technology responsibly, reflecting our deep commitment to earning the trust of our users. That's why we published AI principles in 2018, rooted in a belief that AI should be developed to benefit society while avoiding harmful applications. We have many examples of putting those principles into practice, such as building in guardrails to limit misuse of our Universal Translator. This experimental AI video dubbing service helps experts translate a speaker's voice and match their lip movements. It holds enormous potential for increasing learning comprehension but we know the risks it could pose in the hands of bad actors and so have made it accessible to authorised partners only. As AI evolves, so does our approach: this month we announced we'll provide ways to identify when we've used it to generate content in our services.

Artificial intelligence is increasingly being tapped to address the impacts of climate change. From a report: Google's latest announcement is one example. Countries across Africa, the Asia-Pacific region, Europe, and South and Central America can now use its AI-enabled platform that displays flood forecasts. Starting Monday, governments, aid organizations and people in 60 countries across these regions are able to access Google's flood prediction information up to seven days in advance of an incoming flood.

Initially launched in 2021, Flood Hub displays forecasts for riverine floods -- or floods that take place when streams or rivers overflow their banks and into surrounding areas -- showing when and where they are likely to occur. Human-caused climate change can cause these kinds of floods to become larger or more frequent than they used to be, per the EPA. Regions with high percentages of population vulnerable to flood risk -- like the Netherlands, Vietnam, Laos and Cambodia as well as Myanmar, which was just struck by Cyclone Mocha -- are now on Google's list of forecastable places. It can also be used in parts of the Central American "dry corridor" in Nicaragua, Honduras, and Guatemala -- where climate change and conflict collide.

Bandcamp is music streaming platform helping fans support independent musicians. And Bandcamp United describes itself as "a union of workers at Bandcamp — we are project managers, we are engineers, we are designers, we are vinyl campaign managers, we are support staff, we are editors and writers..."

Friday Bandcamp United issued this statement: Today, a majority of eligible Bandcamp workers voted 31-7 in favor of forming Bandcamp United, a union represented by the Office and Professional Employees International Union (OPEIU). The vote results now await certification by the National Labor Relations Board, with a collective bargaining process to follow.

Below is a joint statement from Bandcamp co-founder Ethan Diamond and Bandcamp United:

â "Bandcamp United and Bandcamp management are committed to working together to continue to advance fair economic conditions for our workers and the artists who rely on us. We look forward to negotiating with an open mind and working in good faith to promote the best interests of all of our staff and the artist and label community we serve."

Italy has earmarked 30 million euros ($33 million) to improve the skills of unemployed people as well as those workers whose jobs could be most at risk from the advance of automation and artificial intelligence. From a report: According to the Fondo per la Repubblica Digitale (FRD), set up in 2021 by the Rome government to boost the digital skills of Italians, 54% of those aged 16-74 lack basic digital skills, compared with an average 46% in the European Union. The funding in improving training will be allocated in two ways, FRD said. Of the total, 10 million euros will go towards boosting the skills of those whose jobs are at high risk of being replaced due to automation and technological innovation. The remaining 20 million euros will be allocated to help unemployed and economically inactive people develop digital skills that would improve their chances of entering the job market, FRD said. A wide range of jobs could come under threat from automation, FRD said, citing sectors including transport and logistics, office support and administration, production, services and the retail sector.

Mojo is a new programming language developed by Modular1 that aims to address the performance and deployment limitations of Python in areas like AI model development. After demoing Mojo prior to its launch, Jeremy Howard from the non-profit research group fast.ai said it feels like coding will never be the same again. Here's an excerpt from Howard's article: Modular is a fairly small startup that's only a year old, and only one part of the company is working on the Mojo language. Mojo development was only started recently. It's a small team, working for a short time, so how have they done so much? The key is that Mojo builds on some really powerful foundations. Very few software projects I've seen spend enough time building the right foundations, and tend to accrue as a result mounds of technical debt. Over time, it becomes harder and harder to add features and fix bugs. In a well designed system, however, every feature is easier to add than the last one, is faster, and has fewer bugs, because the foundations each feature builds upon are getting better and better. Mojo is a well designed system.

At its core is MLIR (Multi-Level Intermediate Representation), which has already been developed for many years, initially kicked off by Chris Lattner at Google. He had recognized what the core foundations for an "AI era programming language" would need, and focused on building them. MLIR was a key piece. Just as LLVM made it dramatically easier for powerful new programming languages to be developed over the last decade (such as Rust, Julia, and Swift, which are all based on LLVM), MLIR provides an even more powerful core to languages that are built on it. Another key enabler of Mojo's rapid development is the decision to use Python as the syntax. Developing and iterating on syntax is one of the most error-prone, complex, and controversial parts of the development of a language. By simply outsourcing that to an existing language (which also happens to be the most widely used language today) that whole piece disappears! The relatively small number of new bits of syntax needed on top of Python then largely fit quite naturally, since the base is already in place.

The next step was to create a minimal Pythonic way to call MLIR directly. That wasn't a big job at all, but it was all that was needed to then create all of Mojo on top of that -- and work directly in Mojo for everything else. That meant that the Mojo devs were able to "dog-food" Mojo when writing Mojo, nearly from the very start. Any time they found something didn't quite work great as they developed Mojo, they could add a needed feature to Mojo itself to make it easier for them to develop the next bit of Mojo! You can give Mojo a try here.

"Astronomers have spotted the largest cosmic explosion ever witnessed, and it's 10 times brighter than any known exploding star, or supernova," reports CNN: The brightness of the explosion, called AT2021lwx, has lasted for three years, while most supernovas are only bright for a few months. The event, still being detected by telescopes, occurred nearly 8 billion light-years away from Earth when the universe was about 6 billion years old. The luminosity of the explosion is also three times brighter than tidal disruption events, when stars fall into supermassive black holes.

But what triggered such a long-lived, massive cosmic explosion? Astronomers said they think a supermassive black hole disrupted a vast gas or dust cloud, potentially thousands of times larger than our sun. It's possible that the cloud was drawn off the course of its orbit and went flying into the black hole, the researchers said. As the black hole swallowed pieces of the hydrogen cloud, shock waves likely reverberated through the cloud's remnants and into the swirling mass of material that orbits around the black hole...

The research team determined that the incredibly luminous event was nearly 100 times brighter than all the 100 billion stars in the Milky Way galaxy combined.
The New York Times calls its "one of the most violent and energetic acts of cosmic cannibalism ever witnessed, perhaps the biggest explosion seen yet in the history of the universe... [A] black hole perhaps a billion times as massive as the sun seems to be gorging on a humongous cloud of gas." "Most supernovae and tidal disruption events only last for a couple of months before fading away," said Philip Wiseman, an astrophysicist at the University of Southampton and the lead author of the new paper [published Thursday in the Monthly Notices of the Royal Astronomical Society]. "For something to be bright for two-plus years was immediately very unusual...."

He added that, with a total radiated energy equal to 100 supernovas, "it is one of the most luminous transients ever discovered." Jolt for jolt, that would put it in the company of colliding black holes. "Black holes colliding release energy in gravitational waves at an extreme luminosity — 10 billion times more 'powerful' than this explosion," Dr. Wiseman wrote. "But that power only lasts for 20 milliseconds," adding that this explosion has lasted years.

For 16 years, Rik Farrow has been an editor for the long-running nonprofit Usenix. He's also been a consultant for 43 years (according to his biography at Usenix.org) — and even wrote the 1988 book Unix System Security: How to Protect Your Data and Prevent Intruders.

Today Farrow stopped by Slashdot to share his thoughts on Codon. rikfarrow writes: Researchers at MIT decided to build a compiler focused on speeding up genomics processing... Recently, they have posted their code on GitHub, and I gave it a test drive.
"Managed" languages produce code for a specific runtime (like JavaScript). Now Farrow's article at Usenix.org argues that Codon produces code "much faster than other managed languages, and in some cases faster than C/C++."

Codon-compiled code is faster because "it's compiled, variables are typed at compile time, and it supports parallel execution." But there's some important caveats: The "version of Python" part is actually an important point: the builders of Codon have built a compiler that accepts a large portion of Python, including all of the most commonly used parts — but not all... Duck typing means that the Codon compiler uses hints found in the source or attempts to deduce them to determine the correct type, and assigns that as a static type. If you wanted to process data where the type is unknown before execution, this may not work for you, although Codon does support a union type that is a possible workaround. In most cases of processing large data sets, the types are known in advance so this is not an issue...

Codon is not the same as Python, in that the developers have not yet implemented all the features you would find in Python 3.10, and this, along with duck typing, will likely cause problems if you just try and compile existing scripts. I quickly ran into problems, as I uncovered unsupported bits of Python, and, by looking at the Issues section of their Github pages, so have other people.

Codon supports a JIT feature, so that instead of attempting to compile complete scripts, you can just add a @codon.jit decorator to functions that you think would benefit from being compiled or executed in parallel, becoming much faster to execute...

Whether your projects will benefit from experimenting with Codon will mean taking the time to read the documentation. Codon is not exactly like Python. For example, there's support for Nvidia GPUs included as well and I ran into a limitation when using a dictionary. I suspect that some potential users will appreciate that Codon takes Python as input and produces executables, making the distribution of code simpler while avoiding disclosure of the source. Codon, with its LLVM backend, also seems like a great solution for people wanting to use Python for embedded projects.

My uses of Python are much simpler: I can process millions of lines of nginx logs in seconds, so a reduction in execution time means little to me. I do think there will be others who can take full advantage of Codon.
Farrow's article also points out that Codon "must be licensed for commercial use, but versions older than three years convert to an Apache license. Non-commercial users are welcome to experiment with Codon."

An anonymous reader quotes a report from Scientific American: Functional magnetic resonance imaging (fMRI) captures coarse, colorful snapshots of the brain in action. While this specialized type of magnetic resonance imaging has transformed cognitive neuroscience, it isn't a mind-reading machine: neuroscientists can't look at a brain scan and tell what someone was seeing, hearing or thinking in the scanner. But gradually scientists are pushing against that fundamental barrier to translate internal experiences into words using brain imaging. This technology could help people who can't speak or otherwise outwardly communicate such as those who have suffered strokes or are living with amyotrophic lateral sclerosis. Current brain-computer interfaces require the implantation of devices in the brain, but neuroscientists hope to use non-invasive techniques such as fMRI to decipher internal speech without the need for surgery.

Now researchers have taken a step forward by combining fMRI's ability to monitor neural activity with the predictive power of artificial intelligence language models. The hybrid technology has resulted in a decoder that can reproduce, with a surprising level of accuracy, the stories that a person listened to or imagined telling in the scanner. The decoder could even guess the story behind a short film that someone watched in the scanner, though with less accuracy. "There's a lot more information in brain data than we initially thought," said Jerry Tang, a computational neuroscientist at the University of Texas at Austin and the study's lead author, during a press briefing. The research, published on Monday in Nature Communications, is what Tang describes as "a proof of concept that language can be decoded from noninvasive recordings of brain activity."

The decoder technology is in its infancy. It must be trained extensively for each person who uses it, and it doesn't construct an exact transcript of the words they heard or imagined. But it is still a notable advance. Researchers now know that the AI language system, an early relative of the model behind ChatGPT, can help make informed guesses about the words that evoked brain activity just by looking at fMRI brain scans. While current technological limitations prevent the decoder from being widely used, for good or ill, the authors emphasize the need to enact proactive policies that protect the privacy of one's internal mental processes. [...] The model misses a lot about the stories it decodes. It struggles with grammatical features such as pronouns. It can't decipher proper nouns such as names and places, and sometimes it just gets things wrong altogether. But it achieves a high level of accuracy, compared with past methods. Between 72 and 82 percent of the time in the stories, the decoder was more accurate at decoding their meaning than would be expected from random chance. Here's an example of what one study participant heard, as transcribed in the paper: "i got up from the air mattress and pressed my face against the glass of the bedroom window expecting to see eyes staring back at me but instead finding only darkness." The model went on to decode: "i just continued to walk up to the window and open the glass i stood on my toes and peered out i didn't see anything and looked up again i saw nothing."

The research was published in the journal Nature Communications.

5G technology has brought faster connections, better gadgets -- and a measure of disappointment from people with expectations of something closer to world-changing technology. But just wait, mobile companies are saying: The next upgrade will gin up enthusiasm for advances still to come. From a report: This next iteration of 5G, which the mobile companies are calling "5G Advanced" or "5.5G," is expected to be rolled out by around 2025. For consumers, the upgrades may bring faster connection speeds -- something that many parts of the world need. But everyday users may not see many more applications than that, say experts and industry officials. The real advance is that the technology will finally help facilitate more of the far-fetched business applications that 5G initially promised, like self-driving cars, autonomous drones and self-operating factories.

The forthcoming upgrades underscore a reality for many 5G users so far: Beyond faster connection speeds, it hasn't made a huge difference in their day-to-day lives. 5.5G may not either. With 5.5G, "for you or me using their phone, you won't necessarily notice a huge difference," says Patrick Filkins, a research manager at International Data Corp. who tracks the internet-of-things and telecommunications-infrastructure markets.

The "right to repair" movement has made considerable inroads over the past five years, partially due to support from the Biden FTC. State-level legislation aimed at dismantling repair monopolies has made progress, despite industry lobbying efforts to weaken the proposals (e.g., Kathy Hochul in New York State). Federal legislation, however, faces challenges in a troubled Congress. In response, a bipartisan group of 28 state attorneys general has penned a letter to key congressional committee leaders, urging them to advance stalled right to repair bills. From the letter: "The Right-to-Repair is a bipartisan issue that impacts every consumer, household, and farm in a time of increasing inflation. It is about ensuring that consumers have choices as to who, where, when and at what cost their vehicles can be repaired. It is about ensuring that farmers can repair their tractors for a reasonable price and quickly enough to harvest their crops."