When AI Asks Dumb Questions, It Gets Smart Fast

sciencehabit shares a report from Science Magazine: If someone showed you a photo of a crocodile and asked whether it was a bird, you might laugh — and then, if you were patient and kind, help them identify the animal. Such real-world, and sometimes dumb, interactions may be key to helping artificial intelligence learn, according to a new study in which the strategy dramatically improved an AI’s accuracy at interpreting novel images. The approach could help AI researchers more quickly design programs that do everything from diagnose disease to direct robots or other devices around homes on their own.

It’s important to think about how AI presents itself, says Kurt Gray, a social psychologist at the University of North Carolina, Chapel Hill, who has studied human-AI interaction but was not involved in the work. “In this case, you want it to be kind of like a kid, right?” he says. Otherwise, people might think you’re a troll for asking seemingly ridiculous questions. The team “rewarded” its AI for writing intelligible questions: When people actually responded to a query, the system received feedback telling it to adjust its inner workings so as to behave similarly in the future. Over time, the AI implicitly picked up lessons in language and social norms, honing its ability to ask questions that were sensical and easily answerable.

The new AI has several components, some of them neural networks, complex mathematical functions inspired by the brain’s architecture. “There are many moving pieces […] that all need to play together,” Krishna says. One component selected an image on Instagram — say a sunset — and a second asked a question about that image — for example, “Is this photo taken at night?” Additional components extracted facts from reader responses and learned about images from them. Across 8 months and more than 200,000 questions on Instagram, the system’s accuracy at answering questions similar to those it had posed increased 118%, the team reports today in the Proceedings of the National Academy of Sciences. A comparison system that posted questions on Instagram but was not explicitly trained to maximize response rates improved its accuracy only 72%, in part because people more frequently ignored it. The main innovation, Jaques says, was rewarding the system for getting humans to respond, “which is not that crazy from a technical perspective, but very important from a research-direction perspective.” She’s also impressed by the large-scale, real-world deployment on Instagram.

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GPS Jammers Are Being Used to Hijack Trucks and Down Drones

The world’s freight-carrying trucks and ships use GPS-based satellite tracking and navigation systems, reports ZDNet. But “Criminals are turning to cheap GPS jamming devices to ransack the cargo on roads and at sea, a problem that’s getting worse….”
Jammers work by overpowering GPS signals by emitting a signal at the same frequency, just a bit more powerful than the original. The typical jammers used for cargo hijackings are able to jam frequencies from up to 5 miles away rendering GPS tracking and security apparatuses, such as those used by trucking syndicates, totally useless. In Mexico, jammers are used in some 85% of cargo truck thefts. Statistics are harder to come by in the United States, but there can be little doubt the devices are prevalent and widely used. Russia is currently availing itself of the technology to jam commercial planes in Ukraine.

As we’ve covered, the proliferating commercial drone sector is also prey to attack…. During a light show in Hong Kong in 2018, a jamming device caused 46 drones to fall out of the sky, raising public awareness of the issue.
While the problem is getting worse, the article also notes that companies are developing anti-jamming solutions for drone receivers, “providing protection and increasing the resiliency of GPS devices against jamming attacks.

“By identifying and preventing instances of jamming, fleet operators are able to prevent cargo theft.”

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Refreezing Earth’s Poles: Feasible and Cheap, New Study Finds

“The poles are warming several times faster than the global average,” Phys.org reminds us, “causing record smashing heatwaves that were reported earlier this year in both the Arctic and Antarctic. Melting ice and collapsing glaciers at high latitudes would accelerate sea level rise around the planet.

“Fortunately, refreezing the poles by reducing incoming sunlight would be both feasible and remarkably cheap, according to new research published Friday in Environmental Research Communications.”

Scientists laid out a possible future program whereby high-flying jets would spray microscopic aerosol particles into the atmosphere at latitudes of 60 degrees north and south — roughly Anchorage and the southern tip of Patagonia. If injected at a height of 43,000 feet (above airliner cruising altitudes), these aerosols would slowly drift poleward, slightly shading the surface beneath. “There is widespread and sensible trepidation about deploying aerosols to cool the planet,” notes lead author Wake Smith, “but if the risk/benefit equation were to pay off anywhere, it would be at the poles.”

Particle injections would be performed seasonally in the long days of the local spring and early summer. The same fleet of jets could service both hemispheres, ferrying to the opposite pole with the change of seasons.
newly designed high-altitude tankers would prove much more efficient. A fleet of roughly 125 such tankers could loft a payload sufficient to cool the regions poleward of 60 degreesN/S by 2 degreesC per year, which would return them close to their pre-industrial average temperatures. Costs are estimated at $11 billion annually — less than one-third the cost of cooling the entire planet by the same 2 degreesC magnitude and a tiny fraction of the cost of reaching net zero emissions.
Smith calls the idea “game-changing” (while also warning it’s “not a substitute for decarbonization”).

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Do America’s Free-Speech Protections Protect Code – and Prevent Cryptocurrency Regulation?

The short answers are “yes” and “no.” America’s Constitution prohibits government intervention into public expression, reports the business-news radio show Marketplace, “protecting free speech and expression “through, for example…. writing, protesting and coding languages like JavaScript, HTML, Python and Perl.”

Specifically protecting code started with the 1995 case of cryptographer Daniel Bernstein, who challenged America’s “export controls” on encryption (which regulated it like a weapon). But they also spoke to technology lawyer Kendra Albert, a clinical instructor at Harvard Law School’s Cyberlaw Clinic, about the specific parameters of how America protects code as a form of expression:
Albert: I think that the reality was that the position that code was a form of expression is in fact supported by a long history of First Amendment law. And that it, you know, is very consistent with how we see the First Amendment interpreted across a variety of contexts…. [O]ne of the questions courts ask is whether a regulation or legislation or a government action is specifically targeting speech, or whether the restrictions on speech are incidental, but not the overall intention. And that’s actually one of the places you see kind of a lot of these difficulties around code as speech. The nature of many kinds of regulation may mean that they restrict code because of the things that particular forms of software code do in the world. But they weren’t specifically meant to restrict the expressive conduct. And courts end up then having to sort of go through a test that was originally developed in the context of someone burning a draft card to figure out — OK, is this regulation, is the burden that it has on this form of expressive speech so significant that we can’t regulate in this way? Or is this just not the focus, and the fact that there are some restrictions on speech as a result of the government attempting to regulate something else should not be the focus of the analysis?
Q: Congress and federal agencies as well as some states are looking to tighten regulations around cryptocurrencies and blockchain technology. What role do you think the idea of code as speech will play in this environment moving forward?

Albert: The reality is that the First Amendment is not a total bar to regulation of speech. It requires the government meet a higher standard for regulating certain kinds of speech. That runs, to some extent, in conflict with how people imagine what “code is speech” does as sort of a total restriction on the regulation of software, of code, because it has expressive content. It just means that we treat code similarly to how we treat other forms of expression, and that the government can regulate them under certain circumstances.

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Apple’s Satellite-Based ‘Emergency SOS’ Prompts Speculation on Future Plans

First, a rumor from the blog Phone Arena. “Not to be outdone by Apple and Huawei, Samsung is planning to incorporate satellite connectivity options in its Galaxy phones as well, hints leakster Ricciolo.”

But it’s not the first rumor we’ve heard about phone vendors and satellites. “Cringley Predicts Apple is About to Create a Satellite-Based IoT Business ,” read the headline in June. Long-time tech pundit Robert X. Cringely predicted that Apple would first offer some limited satellite-based functionality,

But he’d also called those services “proxies for Apple entering — and then dominating — the Internet of Things (IoT) business. “After all, iPhones will give them 1.6 billion points of presence for AirTag detection even on sailboats in the middle of the ocean — or on the South Pole…. Ubiquity (being able to track anything in near real time anywhere on the planet) signals the maturity of IoT, turning it quickly into a $1 TRILLION business — in this case Apple’s $1 TRILLION business.” And beyond that, “in the longer run Cupertino plans to dis-intermediate the mobile carriers — becoming themselves a satellite-based global phone and data company [and] they will also compete with satellite Internet providers like Starlink, OneWeb, and Amazon’s Kuiper.”

So how did Cringely react last week when Apple announced “Emergency SOS” messaging for the iPhone 14 and 14 Plus — via communication satellites — when their users are out of range of a cell signals? He began by wondering if Apple was intentionally downplaying the satellite features:

They limited their usage case to emergency SOS texts in the USA and Canada, sorta said it would be just for iPhone 14s, and be free for only the first two years. They showed a satellite app and very deliberately tried to make it look difficult to use. They gave no technical details and there was no talk of industry partners.

Yet there were hints of what’s to come. We (you and I, based on my previous column) already knew, for example, that ANY iPhone can be made to work with Globalstar. We also knew the deal was with Globalstar, which Apple never mentioned but Globalstar confirmed, more or less, later in the day in an SEC filing. But Apple DID mention Find My and Air Tags, notably saying they’d work through the satellites even without having to first beseech the sky with an app. So the app is less than it seems and Apple’s satellite network will quickly find its use for the Internet of Things [Cringely predicts]….

Apple very specifically said nothing about the global reach of Find My and Air Tags. There is no reason why those services can’t have immediate global satellite support, given that the notification system is entirely within Apple’s ecosystem and is not dependent on 911-type public safety agreements.

Maybe it will take a couple years to cover the world with SOS, but not for Find My, which means not for IoT — a business headed fast toward $1 trillion and will therefore [hypothetically] have a near-immediate impact on Apple’s bottom line.

Speculating further, Cringely predicts that Globalstar — which has ended up with vast tracts of licensed spectrum — will eventually be purchased by a larger company. (“If not Apple, maybe Elon Musk.”)

And this leads Cringely to yet another prediction. “If Elon can’t get Globalstar, he and his partners will push for the regulatory expansion into space of terrestrial 5G licenses, which will probably be successful.”

This will happen, frankly, whether SpaceX and T-Mobile are successful or not, because AST&Science and its investors AT&T, Verizon and Zodafone need 5G in space, too, to compete with Apple. So there WILL eventually be satellite competition for Apple and I think the International Telecommunication Union will eventually succumb to industry pressure.
And by the end Cringely is also speculating about just how Apple will come up with innovative new satellite designs on a faster schedule…

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Ask Slashdot: What Was Your First Computer?

Long-time Slashdot reader destinyland writes: Today GitHub’s official Twitter account asked the ultimate geek-friendly question. “You never forget your first computer. What was yours?”

And within 10 hours they’d gotten 2,700 responses.

Commodore 64, TRS-80, Atari 800, Compaq Presario… People posted names you haven’t heard in years, like they were sharing memories of old friends. Gateway 2000, Sony VAIO, Vic-20, Packard Bell… One person just remembered they’d had “some sort of PC that had an orange and black screen with text and QBasic. It couldn’t do much more than store recipes and play text based games.”

And other memories started to flow. (“Jammed on Commander Keen & Island of Dr. Brain…”
“Dammit that Doom game was amazing, can’t forget Oregon Trail…”)

Sharp PC-4500, Toshiba T3200, Timex Sinclair 1000, NEC PC-8801. Another’s first computer was “A really really old HP laptop that has a broken battery!”

My first computer was an IBM PS/2. It had a 2400 baud internal modem. Though in those long-ago days before local internet services, it was really only good for dialing up BBS’s. I played chess against a program on a floppy disk that I got from a guy from work.

Can you still remember yours? Share your best memories in the comments.

What was your first computer?

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Will AI Really Perform Transformative, Disruptive Miracles?

“An encounter with the superhuman is at hand,” argues Canadian novelist, essayist, and cultural commentator Stephen Marche in an article in the Atlantic titled “Of Gods and Machines”. He argues that GPT-3’s 175 billion parameters give it interpretive power “far beyond human understanding, far beyond what our little animal brains can comprehend. Machine learning has capacities that are real, but which transcend human understanding: the definition of magic.”

But despite being a technology where inscrutability “is an industrial by-product of the process,” we may still not see what’s coming, Marche argue — that AI is “every bit as important and transformative as the other great tech disruptions, but more obscure, tucked largely out of view.”
Science fiction, and our own imagination, add to the confusion. We just can’t help thinking of AI in terms of the technologies depicted in Ex Machina, Her, or Blade Runner — people-machines that remain pure fantasy. Then there’s the distortion of Silicon Valley hype, the general fake-it-’til-you-make-it atmosphere that gave the world WeWork and Theranos: People who want to sound cutting-edge end up calling any automated process “artificial intelligence.” And at the bottom of all of this bewilderment sits the mystery inherent to the technology itself, its direct thrust at the unfathomable. The most advanced NLP programs operate at a level that not even the engineers constructing them fully understand.

But the confusion surrounding the miracles of AI doesn’t mean that the miracles aren’t happening. It just means that they won’t look how anybody has imagined them. Arthur C. Clarke famously said that “technology sufficiently advanced is indistinguishable from magic.” Magic is coming, and it’s coming for all of us….

And if AI harnesses the power promised by quantum computing, everything I’m describing here would be the first dulcet breezes of a hurricane. Ersatz humans are going to be one of the least interesting aspects of the new technology. This is not an inhuman intelligence but an inhuman capacity for digital intelligence. An artificial general intelligence will probably look more like a whole series of exponentially improving tools than a single thing. It will be a whole series of increasingly powerful and semi-invisible assistants, a whole series of increasingly powerful and semi-invisible surveillance states, a whole series of increasingly powerful and semi-invisible weapons systems. The world would change; we shouldn’t expect it to change in any kind of way that you would recognize.

Our AI future will be weird and sublime and perhaps we won’t even notice it happening to us. The paragraph above was composed by GPT-3. I wrote up to “And if AI harnesses the power promised by quantum computing”; machines did the rest.

Stephen Hawking once said that “the development of full artificial intelligence could spell the end of the human race.” Experts in AI, even the men and women building it, commonly describe the technology as an existential threat. But we are shockingly bad at predicting the long-term effects of technology. (Remember when everybody believed that the internet was going to improve the quality of information in the world?) So perhaps, in the case of artificial intelligence, fear is as misplaced as that earlier optimism was.

AI is not the beginning of the world, nor the end. It’s a continuation. The imagination tends to be utopian or dystopian, but the future is human — an extension of what we already are…. Artificial intelligence is returning us, through the most advanced technology, to somewhere primitive, original: an encounter with the permanent incompleteness of consciousness…. They will do things we never thought possible, and sooner than we think. They will give answers that we ourselves could never have provided.

But they will also reveal that our understanding, no matter how great, is always and forever negligible. Our role is not to answer but to question, and to let our questioning run headlong, reckless, into the inarticulate.

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GPU Mining No Longer Profitable After Ethereum Merge

Just one day after the Ethereum Merge, where the cryptocoin successfully switched from Proof of Work (PoW) to Proof of Stake (PoS), profitability of GPU mining has completely collapsed. Tom’s Hardware reports: That means the best graphics cards should finally be back where they belonged, in your gaming PC, just as god intended. That’s a quick drop, considering yesterday there were still a few cryptocurrencies that were technically profitable. Looking at WhatToMine, and using the standard $0.10 per kWh, the best-case results are with the GeForce RTX 3090 and Radeon RX 6800 and 6800 XT. Those are technically showing slightly positive results, to the tune of around $0.06 per day after power costs. However, that doesn’t factor in the cost of the PC power, or the wear and tear on your graphics card.

Even at a slightly positive net result, it would still take over 20 years to break even on the cost of an RX 6800. We say that tongue-in-cheek, because if there’s one thing we know for certain, it’s that no one can predict what the cryptocurrency market will look like even one year out, never mind 20 years in the future. It’s a volatile market, and there are definitely lots of groups and individuals hoping to figure out a way to Make GPU Mining Profitable Again (MGMPA hats inbound…)

Of the 21 current generation graphics cards from the AMD RX 6000-series and the Nvidia RTX 30-series, only five are theoretically profitable right now, and those are all just barely in the black. This is using data from NiceHash and WhatToMine, so perhaps there are ways to tune other GPUs to get into the net positive, but the bottom line is that no one should be using GPUs for mining right now, and certainly not buying more GPUs for mining purposes. [You can see a full list of the current profitability of the current generation graphics cards here.]

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Scientists Try To Teach Robot To Laugh At the Right Time

Laughter comes in many forms, from a polite chuckle to a contagious howl of mirth. Scientists are now developing an AI system that aims to recreate these nuances of humor by laughing in the right way at the right time. The Guardian reports: The team behind the laughing robot, which is called Erica, say that the system could improve natural conversations between people and AI systems. “We think that one of the important functions of conversational AI is empathy,” said Dr Koji Inoue, of Kyoto University, the lead author of the research, published in Frontiers in Robotics and AI. “So we decided that one way a robot can empathize with users is to share their laughter.”

Inoue and his colleagues have set out to teach their AI system the art of conversational laughter. They gathered training data from more than 80 speed-dating dialogues between male university students and the robot, who was initially teleoperated by four female amateur actors. The dialogue data was annotated for solo laughs, social laughs (where humor isn’t involved, such as in polite or embarrassed laughter) and laughter of mirth. This data was then used to train a machine learning system to decide whether to laugh, and to choose the appropriate type. It might feel socially awkward to mimic a small chuckle, but empathetic to join in with a hearty laugh. Based on the audio files, the algorithm learned the basic characteristics of social laughs, which tend to be more subdued, and mirthful laughs, with the aim of mirroring these in appropriate situations.

It might feel socially awkward to mimic a small chuckle, but empathetic to join in with a hearty laugh. Based on the audio files, the algorithm learned the basic characteristics of social laughs, which tend to be more subdued, and mirthful laughs, with the aim of mirroring these in appropriate situations. “Our biggest challenge in this work was identifying the actual cases of shared laughter, which isn’t easy because as you know, most laughter is actually not shared at all,” said Inoue. “We had to carefully categorize exactly which laughs we could use for our analysis and not just assume that any laugh can be responded to.” […] The team said laughter could help create robots with their own distinct character. “We think that they can show this through their conversational behaviours, such as laughing, eye gaze, gestures and speaking style,” said Inoue, although he added that it could take more than 20 years before it would be possible to have a “casual chat with a robot like we would with a friend.” “One of the things I’d keep in mind is that a robot or algorithm will never be able to understand you,” points out Prof Sandra Wachter of the Oxford Internet Institute at the University of Oxford. “It doesn’t know you, it doesn’t understand you and doesn’t understand the meaning of laughter.”

“They’re not sentient, but they might get very good at making you believe they understand what’s going on.”

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Crispr Gene-Editing Drugs Show Promise In Preliminary Study

Intellia Therapeutics reported encouraging early-stage study results for its Crispr gene-editing treatments, the latest sign that the pathbreaking technology could result in commercially available drugs in the coming years. The Wall Street Journal reports: Intellia said Friday that one of its treatments, code-named NTLA-2002, significantly reduced levels of a protein that causes periodic attacks of swelling in six patients with a rare genetic disease called hereditary angioedema, or HAE. In a separate study building on previously released trial data, Intellia’s treatment NTLA-2001 reduced a disease-causing protein by more than 90% in 12 people with transthyretin-mediated amyloidosis cardiomyopathy, or ATTR-CM, a genetic disease that can lead to heart failure.

Despite the positive results, questions remain about whether therapies based on Crispr will work safely and effectively, analysts said. Intellia’s latest studies involved a small number of patients, and were disclosed in news releases and haven’t been published in a peer-reviewed journal. The NTLA-2002 study results were presented at the Bradykinin Symposium in Berlin, a medical meeting focused on angioedema. The data came from small, so-called Phase 1 studies conducted in New Zealand and the U.K. that didn’t include control groups. Results from such early studies can be unreliable predictors of a drug’s safety and effectiveness once the compound is tested in larger numbers of patients. The findings, nevertheless, add to preliminary but promising evidence of the potential for drugs based on the gene-editing technology. Last year, Intellia said that NTLA-2001 reduced the disease-causing protein involved in ATTR patients.

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