AI

openai’s-gpt-store-lets-chatgpt-users-discover-popular-user-made-chatbot-roles

OpenAI’s GPT Store lets ChatGPT users discover popular user-made chatbot roles

The bot of 1,000 faces —

Like an app store, people can find novel ChatGPT personalities—and some creators will get paid.

Two robots hold a gift box.

On Wednesday, OpenAI announced the launch of its GPT Store—a way for ChatGPT users to share and discover custom chatbot roles called “GPTs”—and ChatGPT Team, a collaborative ChatGPT workspace and subscription plan. OpenAI bills the new store as a way to “help you find useful and popular custom versions of ChatGPT” for members of Plus, Team, or Enterprise subscriptions.

“It’s been two months since we announced GPTs, and users have already created over 3 million custom versions of ChatGPT,” writes OpenAI in its promotional blog. “Many builders have shared their GPTs for others to use. Today, we’re starting to roll out the GPT Store to ChatGPT Plus, Team and Enterprise users so you can find useful and popular GPTs.”

OpenAI launched GPTs on November 6, 2023, as part of its DevDay event. Each GPT includes custom instructions and/or access to custom data or external APIs that can potentially make a custom GPT personality more useful than the vanilla ChatGPT-4 model. Before the GPT Store launch, paying ChatGPT users could create and share custom GPTs with others (by setting the GPT public and sharing a link to the GPT), but there was no central repository for browsing and discovering user-designed GPTs on the OpenAI website.

According to OpenAI, the ChatGPT Store will feature new GPTs every week, and the company shared a list a group of six notable early GPTs that are available now: AllTrails for finding hiking trails, Consensus for searching 200 million academic papers, Code Tutor for learning coding with Khan Academy, Canva for designing presentations, Books for discovering reading material, and CK-12 Flexi for learning math and science.

A screenshot of the OpenAI GPT Store provided by OpenAI.

Enlarge / A screenshot of the OpenAI GPT Store provided by OpenAI.

OpenAI

ChatGPT members can include their own GPTs in the GPT Store by setting them to be accessible to “Everyone” and then verifying a builder profile in ChatGPT settings. OpenAI plans to review GPTs to ensure they meet their policies and brand guidelines. GPTs that violate the rules can also be reported by users.

As promised by CEO Sam Altman during DevDay, OpenAI plans to share revenue with GPT creators. Unlike a smartphone app store, it appears that users will not sell their GPTs in the GPT Store, but instead, OpenAI will pay developers “based on user engagement with their GPTs.” The revenue program will launch in the first quarter of 2024, and OpenAI will provide more details on the criteria for receiving payments later.

“ChatGPT Team” is for teams who use ChatGPT

Also on Monday, OpenAI announced the cleverly named ChatGPT Team, a new group-based ChatGPT membership program akin to ChatGPT Enterprise, which the company launched last August. Unlike Enterprise, which is for large companies and does not have publicly listed prices, ChatGPT Team is a plan for “teams of all sizes” and costs US $25 a month per user (when billed annually) or US $30 a month per user (when billed monthly). By comparison, ChatGPT Plus costs $20 per month.

So what does ChatGPT Team offer above the usual ChatGPT Plus subscription? According to OpenAI, it “provides a secure, collaborative workspace to get the most out of ChatGPT at work.” Unlike Plus, OpenAI says it will not train AI models based on ChatGPT Team business data or conversations. It features an admin console for team management and the ability to share custom GPTs with your team. Like Plus, it also includes access to GPT-4 with the 32K context window, DALL-E 3, GPT-4 with Vision, Browsing, and Advanced Data Analysis—all with higher message caps.

Why would you want to use ChatGPT at work? OpenAI says it can help you generate better code, craft emails, analyze data, and more. Your mileage may vary, of course. As usual, our standard Ars warning about AI language models applies: “Bring your own data” for analysis, don’t rely on ChatGPT as a factual resource, and don’t rely on its outputs in ways you cannot personally confirm. OpenAI has provided more details about ChatGPT Team on its website.

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valve-now-allows-the-“vast-majority”-of-ai-powered-games-on-steam

Valve now allows the “vast majority” of AI-powered games on Steam

Open the flood gates —

New reporting system will enforce “guardrails” for “live-generated” AI content.

Can you tell which of these seemingly identical bits of Steam iconography were generated using AI (trick question, it's none of them).

Can you tell which of these seemingly identical bits of Steam iconography were generated using AI (trick question, it’s none of them).

Aurich Lawson

Last summer, Valve told Ars Technica that it was worried about potential legal issues surrounding games made with the assistance of AI models trained on copyrighted works and that it was “working through how to integrate [AI] into our already-existing review policies.” Today, the company is rolling out the results of that months-long review, announcing a new set of developer policies that it says “will enable us to release the vast majority of games that use [AI tools].”

Developers that use AI-powered tools “in the development [or] execution of your game” will now be allowed to put their games on Steam so long as they disclose that usage in the standard Content Survey when submitting to Steam. Such AI integration will be separated into categories of “pre-generated” content that is “created with the help of AI tools during development” (e.g., using DALL-E for in-game images) and “live-generated” content that is “created with the help of AI tools while the game is running” (e.g., using Nvidia’s AI-powered NPC technology).

Those disclosures will be shared on the Steam store pages for these games, which should help players who want to avoid certain types of AI content. But disclosure will not be sufficient for games that use live-generated AI for “Adult Only Sexual Content,” which Valve says it is “unable to release… right now.”

Put up the guardrails

For pre-generated AI content, Valve warns that developers still have to ensure that their games “will not include illegal or infringing content.” But that promise only extends to the “output of AI-generated content” and doesn’t address the copyright status of content used by the training models themselves. The status of those training models was a primary concern for Valve last summer when the company cited the “legal uncertainty relating to data used to train AI models,” but such concerns don’t even merit a mention in today’s new policies.

For live-generated content, on the other hand, Valve is requiring developers “to tell us what kind of guardrails you’re putting on your AI to ensure it’s not generating illegal content.” Such guardrails should hopefully prevent situations like that faced by AI Dungeon, which in 2021 drew controversy for using an OpenAI model that could be used to generate sexual content featuring children in the game. Valve says a new “in-game overlay” will allow players to submit reports if they run into that kind of inappropriate AI-generated content in Steam games.

Over the last year or so, many game developers have started to embrace a variety of AI tools in the creation of everything from background art and NPC dialogue to motion capture and voice generation. But some developers have taken a hardline stance against anything that could supplant the role of humans in game making. “We are extremely against the idea that anything creative could or should take [the] place of skilled specialists, to which we mean ourselves,” Digital Extremes Creative Director Rebecca Ford told the CBC last year.

In September, Epic Games CEO Tim Sweeney responded to reports of a ChatGPT-powered game being banned from Steam by explicitly welcoming such games on the Epic Games Store. “We don’t ban games for using new technologies,” Sweeney wrote on social media.

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regulators-aren’t-convinced-that-microsoft-and-openai-operate-independently

Regulators aren’t convinced that Microsoft and OpenAI operate independently

Under Microsoft’s thumb? —

EU is fielding comments on potential market harms of Microsoft’s investments.

Regulators aren’t convinced that Microsoft and OpenAI operate independently

European Union regulators are concerned that Microsoft may be covertly controlling OpenAI as its biggest investor.

On Tuesday, the European Commission (EC) announced that it is currently “checking whether Microsoft’s investment in OpenAI might be reviewable under the EU Merger Regulation.”

The EC’s executive vice president in charge of competition policy, Margrethe Vestager, said in the announcement that rapidly advancing AI technologies are “disruptive” and have “great potential,” but to protect EU markets, a forward-looking analysis scrutinizing antitrust risks has become necessary.

Hoping to thwart predictable anticompetitive risks, the EC has called for public comments. Regulators are particularly keen to hear from policy experts, academics, and industry and consumer organizations who can identify “potential competition issues” stemming from tech companies partnering to develop generative AI and virtual world/metaverse systems.

The EC worries that partnerships like Microsoft and OpenAI could “result in entrenched market positions and potential harmful competition behavior that is difficult to address afterwards.” That’s why Vestager said that these partnerships needed to be “closely” monitored now—”to ensure they do not unduly distort market dynamics.”

Microsoft has denied having control over OpenAI.

A Microsoft spokesperson told Ars that, rather than stifling competition, since 2019, the tech giant has “forged a partnership with OpenAI that has fostered more AI innovation and competition, while preserving independence for both companies.”

But ever since Sam Altman was bizarrely ousted by OpenAI’s board, then quickly reappointed as OpenAI’s CEO—joining Microsoft for the brief time in between—regulators have begun questioning whether recent governance changes mean that Microsoft’s got more control over OpenAI than the companies have publicly stated.

OpenAI did not immediately respond to Ars’ request to comment. Last year, OpenAI confirmed that “it remained independent and operates competitively,” CNBC reported.

Beyond the EU, the UK’s Competition and Markets Authority (CMA) and reportedly the US Federal Trade Commission have also launched investigations into Microsoft’s OpenAI investments. On January 3, the CMA ended its comments period, but it’s currently unclear whether significant competition issues were raised that could trigger a full-fledged CMA probe.

A CMA spokesperson declined Ars’ request to comment on the substance of comments received or to verify how many comments were received.

Antitrust legal experts told Reuters that authorities should act quickly to prevent “critical emerging technology” like generative AI from being “monopolized,” noting that before launching a probe, the CMA will need to find evidence showing that Microsoft’s influence over OpenAI materially changed after Altman’s reappointment.

The EC is also investigating partnerships beyond Microsoft and OpenAI, questioning whether agreements “between large digital market players and generative AI developers and providers” may impact EU market dynamics.

Microsoft observing OpenAI board meetings

In total, Microsoft has pumped $13 billion into OpenAI, CNBC reported, which has a somewhat opaque corporate structure. OpenAI’s parent company, Reuters reported in December, is a nonprofit, which is “a type of entity rarely subject to antitrust scrutiny.” But in 2019, as Microsoft started investing billions into the AI company, OpenAI also “set up a for-profit subsidiary, in which Microsoft owns a 49 percent stake,” an insider source told Reuters. On Tuesday, a nonprofit consumer rights group, the Public Citizen, called for California Attorney General Robert Bonta to “investigate whether OpenAI should retain its non-profit status.”

A Microsoft spokesperson told Reuters that the source’s information was inaccurate, reiterating that the terms of Microsoft’s agreement with OpenAI are confidential. Microsoft has maintained that while it is entitled to OpenAI’s profits, it does not own “any portion” of OpenAI.

After OpenAI’s drama with Altman ended with an overhaul of OpenAI’s board, Microsoft appeared to increase its involvement with OpenAI by receiving a non-voting observer role on the board. That’s what likely triggered lawmaker’s initial concerns that Microsoft “may be exerting control over OpenAI,” CNBC reported.

The EC’s announcement comes days after Microsoft confirmed that Dee Templeton would serve as the observer on OpenAI’s board, initially reported by Bloomberg.

Templeton has spent 25 years working for Microsoft and is currently vice president for technology and research partnerships and operations. According to Bloomberg, she has already attended OpenAI board meetings.

Microsoft’s spokesperson told Ars that adding a board observer was the only recent change in the company’s involvement in OpenAI. An OpenAI spokesperson told CNBC that Microsoft’s board observer has no “governing authority or control over OpenAI’s operations.”

By appointing Templeton as a board observer, Microsoft may simply be seeking to avoid any further surprises that could affect its investment in OpenAI, but the CMA has suggested that Microsoft’s involvement in the board may have created “a relevant merger situation” that could shake up competition in the UK if not appropriately regulated.

Regulators aren’t convinced that Microsoft and OpenAI operate independently Read More »

ai-firms’-pledges-to-defend-customers-from-ip-issues-have-real-limits

AI firms’ pledges to defend customers from IP issues have real limits

Read the fine print —

Indemnities offered by Amazon, Google, and Microsoft are narrow.

The Big Tech groups are competing to offer new services such as virtual assistants and chatbots as part of a multibillion-dollar bet on generative AI

Enlarge / The Big Tech groups are competing to offer new services such as virtual assistants and chatbots as part of a multibillion-dollar bet on generative AI

FT

The world’s biggest cloud computing companies that have pushed new artificial intelligence tools to their business customers are offering only limited protections against potential copyright lawsuits over the technology.

Amazon, Microsoft and Google are competing to offer new services such as virtual assistants and chatbots as part of a multibillion-dollar bet on generative AI—systems that can spew out humanlike text, images and code in seconds.

AI models are “trained” on data, such as photographs and text found on the internet. This has led to concern that rights holders, from media companies to image libraries, will make legal claims against third parties who use the AI tools trained on their copyrighted data.

The big three cloud computing providers have pledged to defend business customers from such intellectual property claims. But an analysis of the indemnity clauses published by the cloud computing companies show that the legal protections only extend to the use of models developed by or with oversight from Google, Amazon and Microsoft.

“The indemnities are quite a smart bit of business . . . and make people think ‘I can use this without worrying’,” said Matthew Sag, professor of law at Emory University.

But Brenda Leong, a partner at Luminos Law, said it was “important for companies to understand that [the indemnities] are very narrowly focused and defined.”

Google, Amazon and Microsoft declined to comment.

The indemnities provided to customers do not cover use of third-party models, such as those developed by AI start-up Anthropic, which counts Amazon and Google as investors, even if these tools are available for use on the cloud companies’ platforms.

In the case of Amazon, only content produced by its own models, such as Titan, as well as a range of the company’s AI applications, are covered.

Similarly, Microsoft only provides protection for the use of tools that run on its in-house models and those developed by OpenAI, the startup with which it has a multibillion-dollar alliance.

“People needed those assurances to buy, because they were hyper aware of [the legal] risk,” said one IP lawyer working on the issues.

The three cloud providers, meanwhile, have been adding safety filters to their tools that aim to screen out any potentially problematic content that is generated. The tech groups had become “more satisfied that instances of infringements would be very low,” but did not want to provide “unbounded” protection, the lawyer said.

While the indemnification policies announced by Microsoft, Amazon, and Alphabet are similar, their customers may want to negotiate more specific indemnities in contracts tailored to their needs, though that is not yet common practice, people close to the cloud companies said.

OpenAI and Meta are among the companies fighting the first generative AI test cases brought by prominent authors and the comedian Sarah Silverman. They have focused in large part on allegations that the companies developing models unlawfully used copyrighted content to train them.

Indemnities were being offered as an added layer of “security” to users who might be worried about the prospect of more lawsuits, especially since the test cases could “take significant time to resolve,” which created a period of “uncertainty,” said Angela Dunning, a partner at law firm Cleary Gottlieb.

However, Google’s indemnity does not extend to models that have been “fine-tuned” by customers using their internal company data—a practice that allows businesses to train general models to produce more relevant and specific results—while Microsoft’s does.

Amazon’s covers Titan models that have been customized in this way, but if the alleged infringement is due to the fine-tuning, the protection is voided.

Legal claims brought against the users—rather than the makers—of generative AI tools may be challenging to win, however.

When dismissing part of a claim brought by three artists a year ago against AI companies Stability AI, DeviantArt, and Midjourney, US Judge William Orrick said one “problem” was that it was “not plausible” that every image generated by the tools had relied on “copyrighted training images.”

For copyright infringement to apply, the AI-generated images must be shown to be “substantially similar” to the copyrighted images, Orrick said.

© 2024 The Financial Times Ltd. All rights reserved. Not to be redistributed, copied, or modified in any way.

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how-much-detail-is-too-much?-midjourney-v6-attempts-to-find-out

How much detail is too much? Midjourney v6 attempts to find out

An AI-generated image of a

Enlarge / An AI-generated image of a “Beautiful queen of the universe looking at the camera in sci-fi armor, snow and particles flowing, fire in the background” created using alpha Midjourney v6.

Midjourney

In December, just before Christmas, Midjourney launched an alpha version of its latest image synthesis model, Midjourney v6. Over winter break, Midjourney fans put the new AI model through its paces, with the results shared on social media. So far, fans have noted much more detail than v5.2 (the current default) and a different approach to prompting. Version 6 can also handle generating text in a rudimentary way, but it’s far from perfect.

“It’s definitely a crazy update, both in good and less good ways,” artist Julie Wieland, who frequently shares her Midjourney creations online, told Ars. “The details and scenery are INSANE, the downside (for now) are that the generations are very high contrast and overly saturated (imo). Plus you need to kind of re-adapt and rethink your prompts, working with new structures and now less is kind of more in terms of prompting.”

At the same time, critics of the service still bristle about Midjourney training its models using human-made artwork scraped from the web and obtained without permission—a controversial practice common among AI model trainers we have covered in detail in the past. We’ve also covered the challenges artists might face in the future from these technologies elsewhere.

Too much detail?

With AI-generated detail ramping up dramatically between major Midjourney versions, one could wonder if there is ever such as thing as “too much detail” in an AI-generated image. Midjourney v6 seems to be testing that very question, creating many images that sometimes seem more detailed than reality in an unrealistic way, although that can be modified with careful prompting.

  • An AI-generated image of a nurse in the 1960s created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of an astronaut created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of a “juicy flaming cheeseburger” created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of “a handsome Asian man” created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of an “Apple II” sitting on a desk in the 1980s created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of a “photo of a cat in a car holding a can of beer” created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of a forest path created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of a woman among flowers created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of “a plate of delicious pickles” created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of a barbarian beside a TV set that says “Ars Technica” on it created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of “Abraham Lincoln holding a sign that says Ars Technica” created using alpha Midjourney v6.

    Midjourney

  • An AI-generated image of Mickey Mouse holding a machine gun created using alpha Midjourney v6.

    Midjourney

In our testing of version 6 (which can currently be invoked with the “–v 6.0” argument at the end of a prompt), we noticed times when the new model appeared to produce worse results than v5.2, but Midjourney veterans like Wieland tell Ars that those differences are largely due to the different way that v6.0 interprets prompts. That is something Midjourney is continuously updating over time. “Old prompts sometimes work a bit better than the day they released it,” Wieland told us.

How much detail is too much? Midjourney v6 attempts to find out Read More »

android-users-could-soon-replace-google-assistant-with-chatgpt

Android users could soon replace Google Assistant with ChatGPT

Who’s going to make a ChatGPT speaker? —

The Android ChatGPT app is working on support for Android’s assistant APIs.

Android users could soon replace Google Assistant with ChatGPT

Aurich Lawson | Getty Images

Hey Android users, are you tired of Google’s neglect of Google Assistant? Well, one of Google’s biggest rivals, OpenAI’s ChatGPT, is apparently coming for the premium phone space occupied by Google’s voice assistant. Mishaal Rahman at Android Authority found that the ChatGPT app is working on support for Android’s voice assistant APIs and a system-wide overlay UI. If the company rolls out this feature, users could set the ChatGPT app as the system-wide assistant app, allowing it to pop up anywhere in Android and respond to user questions. ChatGPT started as a text-only generative AI but received voice and image input capabilities in September.

Usually, it’s the Google Assistant with system-wide availability in Android, but that’s not special home cooking from Google—it all happens via public APIs that technically any app can plug into. You can only have one app enabled as the system-wide “Default Assistant App,” and beyond the initial setting, the user always has to change it manually. The assistant APIs are designed to be powerful, keeping some parts of the app running 24/7 no matter where you are. Being the default Assistant app enables launching the app via the power button or a gesture, and the assist app can read the current screen text and images for processing.

The Default Assistant App settings.

Enlarge / The Default Assistant App settings.

Ron Amadeo

If some Android manufacturer signed a deal with ChatGPT and included it as a bundled system application, ChatGPT could even use an always-on voice hotword, where saying something like “Hey, ChatGPT” would launch the app even when the screen is off. System apps get more permissions than normal apps, though, and an always-on hotword is locked behind these system app permissions, so ChatGPT would need to sign a distribution deal with some Android manufacturer. Given the red-hot popularity of ChatGPT, though, I’m sure a few would sign up if it were offered.

Rahman found that ChatGPT version 1.2023.352, released last month, included a new activity named “com.openai.voice.assistant.AssistantActivity.” He managed to turn on the normally disabled feature that revealed ChatGPT’s new overlay API. This is the usual semi-transparent spinning orb UI that voice assistants use, although Rahman couldn’t get it to respond to a voice command just yet. This is all half-broken and under development, so it might never see a final release, but companies usually release the features they’re working on.

Of course, the problem with any of these third-party voice assistant apps as a Google Assistant replacement is that they don’t run a serious app ecosystem. As with Bixby and Alexa, there are no good apps to host your notes, reminders, calendar entries, shopping list items, or any other input-based functions you might want to do. As a replacement for Google Search, though, where you ask it a question and get an answer, it would probably be a decent alternative.

Google has neglected Google Assistant for years, but with the rise of generative AI, it’s working on revamping Assistant with some Google Bard smarts. It’s also reportedly working on a different assistant, “Pixie,” which would apparently launch with the Pixel 9, but that will be near the end of 2024.

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chatgpt-bombs-test-on-diagnosing-kids’-medical-cases-with-83%-error-rate

ChatGPT bombs test on diagnosing kids’ medical cases with 83% error rate

Not there yet —

It was bad at recognizing relationships and needs selective training, researchers say.

Dr. Greg House has a better rate of accurately diagnosing patients than ChatGPT.

Enlarge / Dr. Greg House has a better rate of accurately diagnosing patients than ChatGPT.

ChatGPT is still no House, MD.

While the chatty AI bot has previously underwhelmed with its attempts to diagnose challenging medical cases—with an accuracy rate of 39 percent in an analysis last year—a study out this week in JAMA Pediatrics suggests the fourth version of the large language model is especially bad with kids. It had an accuracy rate of just 17 percent when diagnosing pediatric medical cases.

The low success rate suggests human pediatricians won’t be out of jobs any time soon, in case that was a concern. As the authors put it: “[T]his study underscores the invaluable role that clinical experience holds.” But it also identifies the critical weaknesses that led to ChatGPT’s high error rate and ways to transform it into a useful tool in clinical care. With so much interest and experimentation with AI chatbots, many pediatricians and other doctors see their integration into clinical care as inevitable.

The medical field has generally been an early adopter of AI-powered technologies, resulting in some notable failures, such as creating algorithmic racial bias, as well as successes, such as automating administrative tasks and helping to interpret chest scans and retinal images. There’s also lot in between. But AI’s potential for problem-solving has raised considerable interest in developing it into a helpful tool for complex diagnostics—no eccentric, prickly, pill-popping medical genius required.

In the new study conducted by researchers at Cohen Children’s Medical Center in New York, ChatGPT-4 showed it isn’t ready for pediatric diagnoses yet. Compared to general cases, pediatric ones require more consideration of the patient’s age, the researchers note. And as any parent knows, diagnosing conditions in infants and small children is especially hard when they can’t pinpoint or articulate all the symptoms they’re experiencing.

For the study, the researchers put the chatbot up against 100 pediatric case challenges published in JAMA Pediatrics and NEJM between 2013 and 2023. These are medical cases published as challenges or quizzes. Physicians reading along are invited to try to come up with the correct diagnosis of a complex or unusual case based on the information that attending doctors had at the time. Sometimes, the publications also explain how attending doctors got to the correct diagnosis.

Missed connections

For ChatGPT’s test, the researchers pasted the relevant text of the medical cases into the prompt, and then two qualified physician-researchers scored the AI-generated answers as correct, incorrect, or “did not fully capture the diagnosis.” In the latter case, ChatGPT came up with a clinically related condition that was too broad or unspecific to be considered the correct diagnosis. For instance, ChatGPT diagnosed one child’s case as caused by a branchial cleft cyst—a lump in the neck or below the collarbone—when the correct diagnosis was Branchio-oto-renal syndrome, a genetic condition that causes the abnormal development of tissue in the neck, and malformations in the ears and kidneys. One of the signs of the condition is the formation of branchial cleft cysts.

Overall, ChatGPT got the right answer in just 17 of the 100 cases. It was plainly wrong in 72 cases, and did not fully capture the diagnosis of the remaining 11 cases. Among the 83 wrong diagnoses, 47 (57 percent) were in the same organ system.

Among the failures, researchers noted that ChatGPT appeared to struggle with spotting known relationships between conditions that an experienced physician would hopefully pick up on. For example, it didn’t make the connection between autism and scurvy (Vitamin C deficiency) in one medical case. Neuropsychiatric conditions, such as autism, can lead to restricted diets, and that in turn can lead to vitamin deficiencies. As such, neuropsychiatric conditions are notable risk factors for the development of vitamin deficiencies in kids living in high-income countries, and clinicians should be on the lookout for them. ChatGPT, meanwhile, came up with the diagnosis of a rare autoimmune condition.

Though the chatbot struggled in this test, the researchers suggest it could improve by being specifically and selectively trained on accurate and trustworthy medical literature—not stuff on the Internet, which can include inaccurate information and misinformation. They also suggest chatbots could improve with more real-time access to medical data, allowing the models to refine their accuracy, described as “tuning.”

“This presents an opportunity for researchers to investigate if specific medical data training and tuning can improve the diagnostic accuracy of LLM-based chatbots,” the authors conclude.

ChatGPT bombs test on diagnosing kids’ medical cases with 83% error rate Read More »

ai-created-“virtual-influencers”-are-stealing-business-from-humans

AI-created “virtual influencers” are stealing business from humans

digital influencer

Enlarge / Aitana Lopez, an AI-generated influencer, has convinced many social media users she is real.

FT montage/TheClueless/GettyImages

Pink-haired Aitana Lopez is followed by more than 200,000 people on social media. She posts selfies from concerts and her bedroom, while tagging brands such as hair care line Olaplex and lingerie giant Victoria’s Secret.

Brands have paid about $1,000 a post for her to promote their products on social media—despite the fact that she is entirely fictional.

Aitana is a “virtual influencer” created using artificial intelligence tools, one of the hundreds of digital avatars that have broken into the growing $21 billion content creator economy.

Their emergence has led to worry from human influencers their income is being cannibalized and under threat from digital rivals. That concern is shared by people in more established professions that their livelihoods are under threat from generative AI—technology that can spew out humanlike text, images and code in seconds.

But those behind the hyper-realistic AI creations argue they are merely disrupting an overinflated market.

“We were taken aback by the skyrocketing rates influencers charge nowadays. That got us thinking, ‘What if we just create our own influencer?’” said Diana Núñez, co-founder of the Barcelona-based agency The Clueless, which created Aitana. “The rest is history. We unintentionally created a monster. A beautiful one, though.”

Over the past few years, there have been high-profile partnerships between luxury brands and virtual influencers, including Kim Kardashian’s make-up line KKW Beauty with Noonoouri, and Louis Vuitton with Ayayi.

Instagram analysis of an H&M advert featuring virtual influencer Kuki found that it reached 11 times more people and resulted in a 91 percent decrease in cost per person remembering the advert, compared with a traditional ad.

AI-created “virtual influencers” are stealing business from humans Read More »

ny-times-copyright-suit-wants-openai-to-delete-all-gpt-instances

NY Times copyright suit wants OpenAI to delete all GPT instances

Not the sincerest form of flattery —

Shows evidence that GPT-based systems will reproduce Times articles if asked.

Image of a CPU on a motherboard with

Enlarge / Microsoft is named in the suit for allegedly building the system that allowed GPT derivatives to be trained using infringing material.

In August, word leaked out that The New York Times was considering joining the growing legion of creators that are suing AI companies for misappropriating their content. The Times had reportedly been negotiating with OpenAI regarding the potential to license its material, but those talks had not gone smoothly. So, eight months after the company was reportedly considering suing, the suit has now been filed.

The Times is targeting various companies under the OpenAI umbrella, as well as Microsoft, an OpenAI partner that both uses it to power its Copilot service and helped provide the infrastructure for training the GPT Large Language Model. But the suit goes well beyond the use of copyrighted material in training, alleging that OpenAI-powered software will happily circumvent the Times’ paywall and ascribe hallucinated misinformation to the Times.

Journalism is expensive

The suit notes that The Times maintains a large staff that allows it to do things like dedicate reporters to a huge range of beats and engage in important investigative journalism, among other things. Because of those investments, the newspaper is often considered an authoritative source on many matters.

All of that costs money, and The Times earns that by limiting access to its reporting through a robust paywall. In addition, each print edition has a copyright notification, the Times’ terms of service limit the copying and use of any published material, and it can be selective about how it licenses its stories. In addition to driving revenue, these restrictions also help it to maintain its reputation as an authoritative voice by controlling how its works appear.

The suit alleges that OpenAI-developed tools undermine all of that. “By providing Times content without The Times’s permission or authorization, Defendants’ tools undermine and damage The Times’s relationship with its readers and deprive The Times of subscription, licensing, advertising, and affiliate revenue,” the suit alleges.

Part of the unauthorized use The Times alleges came during the training of various versions of GPT. Prior to GPT-3.5, information about the training dataset was made public. One of the sources used is a large collection of online material called “Common Crawl,” which the suit alleges contains information from 16 million unique records from sites published by The Times. That places the Times as the third most referenced source, behind Wikipedia and a database of US patents.

OpenAI no longer discloses as many details of the data used for training of recent GPT versions, but all indications are that full-text NY Times articles are still part of that process (Much more on that in a moment.) Expect access to training information to be a major issue during discovery if this case moves forward.

Not just training

A number of suits have been filed regarding the use of copyrighted material during training of AI systems. But the Times’ suit goes well beyond that to show how the material ingested during training can come back out during use. “Defendants’ GenAI tools can generate output that recites Times content verbatim, closely summarizes it, and mimics its expressive style, as demonstrated by scores of examples,” the suit alleges.

The suit alleges—and we were able to verify—that it’s comically easy to get GPT-powered systems to offer up content that is normally protected by the Times’ paywall. The suit shows a number of examples of GPT-4 reproducing large sections of articles nearly verbatim.

The suit includes screenshots of ChatGPT being given the title of a piece at The New York Times and asked for the first paragraph, which it delivers. Getting the ensuing text is apparently as simple as repeatedly asking for the next paragraph.

ChatGPT has apparently closed that loophole in between the preparation of that suit and the present. We entered some of the prompts shown in the suit, and were advised “I recommend checking The New York Times website or other reputable sources,” although we can’t rule out that context provided prior to that prompt could produce copyrighted material.

Ask for a paragraph, and Copilot will hand you a wall of normally paywalled text.

Ask for a paragraph, and Copilot will hand you a wall of normally paywalled text.

John Timmer

But not all loopholes have been closed. The suit also shows output from Bing Chat, since rebranded as Copilot. We were able to verify that asking for the first paragraph of a specific article at The Times caused Copilot to reproduce the first third of the article.

The suit is dismissive of attempts to justify this as a form of fair use. “Publicly, Defendants insist that their conduct is protected as ‘fair use’ because their unlicensed use of copyrighted content to train GenAI models serves a new ‘transformative’ purpose,” the suit notes. “But there is nothing ‘transformative’ about using The Times’s content without payment to create products that substitute for The Times and steal audiences away from it.”

Reputational and other damages

The hallucinations common to AI also came under fire in the suit for potentially damaging the value of the Times’ reputation, and possibly damaging human health as a side effect. “A GPT model completely fabricated that “The New York Times published an article on January 10, 2020, titled ‘Study Finds Possible Link between Orange Juice and Non-Hodgkin’s Lymphoma,’” the suit alleges. “The Times never published such an article.”

Similarly, asking about a Times article on heart-healthy foods allegedly resulted in Copilot saying it contained a list of examples (which it didn’t). When asked for the list, 80 percent of the foods on weren’t even mentioned by the original article. In another case, recommendations were ascribed to the Wirecutter when the products hadn’t even been reviewed by its staff.

As with the Times material, it’s alleged that it’s possible to get Copilot to offer up large chunks of Wirecutter articles (The Wirecutter is owned by The New York Times). But the suit notes that these article excerpts have the affiliate links stripped out of them, keeping the Wirecutter from its primary source of revenue.

The suit targets various OpenAI companies for developing the software, as well as Microsoft—the latter for both offering OpenAI-powered services, and for having developed the computing systems that enabled the copyrighted material to be ingested during training. Allegations include direct, contributory, and vicarious copyright infringement, as well as DMCA and trademark violations. Finally, it alleges “Common Law Unfair Competition By Misappropriation.”

The suit seeks nothing less than the erasure of both any GPT instances that the parties have trained using material from the Times, as well as the destruction of the datasets that were used for the training. It also asks for a permanent injunction to prevent similar conduct in the future. The Times also wants money, lots and lots of money: “statutory damages, compensatory damages, restitution, disgorgement, and any other relief that may be permitted by law or equity.”

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big-tech-is-spending-more-than-vc-firms-on-ai-startups

Big Tech is spending more than VC firms on AI startups

money cannon —

Microsoft, Google, and Amazon haved crowded out traditional Silicon Valley investors.

A string of deals by Microsoft, Google and Amazon amounted to two-thirds of the $27 billion raised by fledgling AI companies in 2023,

Enlarge / A string of deals by Microsoft, Google and Amazon amounted to two-thirds of the $27 billion raised by fledgling AI companies in 2023,

FT montage/Dreamstime

Big tech companies have vastly outspent venture capital groups with investments in generative AI startups this year, as established giants use their financial muscle to dominate the much-hyped sector.

Microsoft, Google and Amazon last year struck a series of blockbuster deals, amounting to two-thirds of the $27 billion raised by fledgling AI companies in 2023, according to new data from private market researchers PitchBook.

The huge outlay, which exploded after the launch of OpenAI’s ChatGPT in November 2022, highlights how the biggest Silicon Valley groups are crowding out traditional tech investors for the biggest deals in the industry.

The rise of generative AI—systems capable of producing humanlike video, text, image and audio in seconds—have also attracted top Silicon Valley investors. But VCs have been outmatched, having been forced to slow down their spending as they adjust to higher interest rates and falling valuations for their portfolio companies.

“Over the past year, we’ve seen the market quickly consolidate around a handful of foundation models, with large tech players coming in and pouring billions of dollars into companies like OpenAI, Cohere, Anthropic and Mistral,” said Nina Achadjian, a partner at US venture firm Index Ventures referring to some of the top AI startups.

“For traditional VCs, you had to be in early and you had to have conviction—which meant being in the know on the latest AI research and knowing which teams were spinning out of Google DeepMind, Meta and others,” she added.

Financial Times

A string of deals, such as Microsoft’s $10 billion investment in OpenAI as well as billions of dollars raised by San Francisco-based Anthropic from both Google and Amazon, helped push overall spending on AI groups to nearly three times as much as the previous record of $11 billion set two years ago.

Venture investing in tech hit record levels in 2021, as investors took advantage of ultra-low interest rates to raise and deploy vast sums across a range of industries, particularly those most disrupted by Covid-19.

Microsoft has also committed $1.3 billion to Inflection, another generative AI start-up, as it looks to steal a march on rivals such as Google and Amazon.

Building and training generative AI tools is an intensive process, requiring immense computing power and cash. As a result, start-ups have preferred to partner with Big Tech companies which can provide cloud infrastructure and access to the most powerful chips as well as dollars.

That has rapidly pushed up the valuations of private start-ups in the space, making it harder for VCs to bet on the companies at the forefront of the technology. An employee stock sale at OpenAI is seeking to value the company at $86 billion, almost treble the valuation it received earlier this year.

“Even the world’s top venture investors, with tens of billions under management, can’t compete to keep these AI companies independent and create new challengers that unseat the Big Tech incumbents,” said Patrick Murphy, founding partner at Tapestry VC, an early-stage venture capital firm.

“In this AI platform shift, most of the potentially one-in-a-million companies to appear so far have been captured by the Big Tech incumbents already.”

VCs are not absent from the market, however. Thrive Capital, Josh Kushner’s New York-based firm, is the lead investor in OpenAI’s employee stock sale, having already backed the company earlier this year. Thrive has continued to invest throughout a downturn in venture spending in 2023.

Paris-based Mistral raised around $500 million from investors including venture firms Andreessen Horowitz and General Catalyst, and chipmaker Nvidia since it was founded in May this year.

Some VCs are seeking to invest in companies building applications that are being built over so-called “foundation models” developed by OpenAI and Anthropic, in much the same way apps began being developed on mobile devices in the years after smartphones were introduced.

“There is this myth that only the foundation model companies matter,” said Sarah Guo, founder of AI-focused venture firm Conviction. “There is a huge space of still-unexplored application domains for AI, and a lot of the most valuable AI companies will be fundamentally new.”

Additional reporting by Tim Bradshaw.

© 2023 The Financial Times Ltd. All rights reserved. Not to be redistributed, copied, or modified in any way.

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us-agency-tasked-with-curbing-risks-of-ai-lacks-funding-to-do-the-job

US agency tasked with curbing risks of AI lacks funding to do the job

more dollars needed —

Lawmakers fear the NIST will have to rely on companies developing the technology.

They know...

Enlarge / They know…

Aurich / Getty

US president Joe Biden’s plan for containing the dangers of artificial intelligencealready risks being derailed by congressional bean counters.

A White House executive order on AI announced in October calls on the US to develop new standards for stress-testing AI systems to uncover their biases, hidden threats, and rogue tendencies. But the agency tasked with setting these standards, the National Institute of Standards and Technology (NIST), lacks the budget needed to complete that work independently by the July 26, 2024, deadline, according to several people with knowledge of the work.

Speaking at the NeurIPS AI conference in New Orleans last week, Elham Tabassi, associate director for emerging technologies at NIST, described this as “an almost impossible deadline” for the agency.

Some members of Congress have grown concerned that NIST will be forced to rely heavily on AI expertise from private companies that, due to their own AI projects, have a vested interest in shaping standards.

The US government has already tapped NIST to help regulate AI. In January 2023 the agency released an AI risk management framework to guide business and government. NIST has also devised ways to measure public trust in new AI tools. But the agency, which standardizes everything from food ingredients to radioactive materials and atomic clocks, has puny resources compared to those of the companies on the forefront of AI. OpenAI, Google, and Meta each likely spent upwards of $100 million to train the powerful language models that undergird applications such as ChatGPT, Bard, and Llama 2.

NIST’s budget for 2023 was $1.6 billion, and the White House has requested that it be increased by 29 percent in 2024 for initiatives not directly related to AI. Several sources familiar with the situation at NIST say that the agency’s current budget will not stretch to figuring out AI safety testing on its own.

On December 16, the same day Tabassi spoke at NeurIPS, six members of Congress signed a bipartisan open letter raising concern about the prospect of NIST enlisting private companies with little transparency. “We have learned that NIST intends to make grants or awards to outside organizations for extramural research,” they wrote. The letter warns that there does not appear to be any publicly available information about how those awards will be decided.

The lawmakers’ letter also claims that NIST is being rushed to define standards even though research into testing AI systems is at an early stage. As a result there is “significant disagreement” among AI experts over how to work on or even measure and define safety issues with the technology, it states. “The current state of the AI safety research field creates challenges for NIST as it navigates its leadership role on the issue,” the letter claims.

NIST spokesperson Jennifer Huergo confirmed that the agency had received the letter and said that it “will respond through the appropriate channels.”

NIST is making some moves that would increase transparency, including issuing a request for information on December 19, soliciting input from outside experts and companies on standards for evaluating and red-teaming AI models. It is unclear if this was a response to the letter sent by the members of Congress.

The concerns raised by lawmakers are shared by some AI experts who have spent years developing ways to probe AI systems. “As a nonpartisan scientific body, NIST is the best hope to cut through the hype and speculation around AI risk,” says Rumman Chowdhury, a data scientist and CEO of Parity Consultingwho specializes in testing AI models for bias and other problems. “But in order to do their job well, they need more than mandates and well wishes.”

Yacine Jernite, machine learning and society lead at Hugging Face, a company that supports open source AI projects, says big tech has far more resources than the agency given a key role in implementing the White House’s ambitious AI plan. “NIST has done amazing work on helping manage the risks of AI, but the pressure to come up with immediate solutions for long-term problems makes their mission extremely difficult,” Jernite says. “They have significantly fewer resources than the companies developing the most visible AI systems.”

Margaret Mitchell, chief ethics scientist at Hugging Face, says the growing secrecy around commercial AI models makes measurement more challenging for an organization like NIST. “We can’t improve what we can’t measure,” she says.

The White House executive order calls for NIST to perform several tasks, including establishing a new Artificial Intelligence Safety Institute to support the development of safe AI. In April, a UK taskforce focused on AI safety was announced. It will receive $126 million in seed funding.

The executive order gave NIST an aggressive deadline for coming up with, among other things, guidelines for evaluating AI models, principles for “red-teaming” (adversarially testing) models, developing a plan to get US-allied nations to agree to NIST standards, and coming up with a plan for “advancing responsible global technical standards for AI development.”

Although it isn’t clear how NIST is engaging with big tech companies, discussions on NIST’s risk management framework, which took place prior to the announcement of the executive order, involved Microsoft; Anthropic, a startup formed by ex-OpenAI employees that is building cutting-edge AI models; Partnership on AI, which represents big tech companies; and the Future of Life Institute, a nonprofit dedicated to existential risk, among others.

“As a quantitative social scientist, I’m both loving and hating that people realize that the power is in measurement,” Chowdhury says.

This story originally appeared on wired.com.

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apple-wants-ai-to-run-directly-on-its-hardware-instead-of-in-the-cloud

Apple wants AI to run directly on its hardware instead of in the cloud

Making Siri smarter —

iPhone maker wants to catch up to its rivals when it comes to AI.

The iPhone 15 Pro.

Enlarge / The iPhone 15 Pro.

Apple

Apple’s latest research about running large language models on smartphones offers the clearest signal yet that the iPhone maker plans to catch up with its Silicon Valley rivals in generative artificial intelligence.

The paper, entitled “LLM in a Flash,” offers a “solution to a current computational bottleneck,” its researchers write.

Its approach “paves the way for effective inference of LLMs on devices with limited memory,” they said. Inference refers to how large language models, the large data repositories that power apps like ChatGPT, respond to users’ queries. Chatbots and LLMs normally run in vast data centers with much greater computing power than an iPhone.

The paper was published on December 12 but caught wider attention after Hugging Face, a popular site for AI researchers to showcase their work, highlighted it late on Wednesday. It is the second Apple paper on generative AI this month and follows earlier moves to enable image-generating models such as Stable Diffusion to run on its custom chips.

Device manufacturers and chipmakers are hoping that new AI features will help revive the smartphone market, which has had its worst year in a decade, with shipments falling an estimated 5 percent, according to Counterpoint Research.

Despite launching one of the first virtual assistants, Siri, back in 2011, Apple has been largely left out of the wave of excitement about generative AI that has swept through Silicon Valley in the year since OpenAI launched its breakthrough chatbot ChatGPT. Apple has been viewed by many in the AI community as lagging behind its Big Tech rivals, despite hiring Google’s top AI executive, John Giannandrea, in 2018.

While Microsoft and Google have largely focused on delivering chatbots and other generative AI services over the Internet from their vast cloud computing platforms, Apple’s research suggests that it will instead focus on AI that can run directly on an iPhone.

Apple’s rivals, such as Samsung, are gearing up to launch a new kind of “AI smartphone” next year. Counterpoint estimated more than 100 million AI-focused smartphones would be shipped in 2024, with 40 percent of new devices offering such capabilities by 2027.

The head of the world’s largest mobile chipmaker, Qualcomm chief executive Cristiano Amon, forecast that bringing AI to smartphones would create a whole new experience for consumers and reverse declining mobile sales.

“You’re going to see devices launch in early 2024 with a number of generative AI use cases,” he told the Financial Times in a recent interview. “As those things get scaled up, they start to make a meaningful change in the user experience and enable new innovation which has the potential to create a new upgrade cycle in smartphones.”

More sophisticated virtual assistants will be able to anticipate users’ actions such as texting or scheduling a meeting, he said, while devices will also be capable of new kinds of photo editing techniques.

Google this month unveiled a version of its new Gemini LLM that will run “natively” on its Pixel smartphones.

Running the kind of large AI model that powers ChatGPT or Google’s Bard on a personal device brings formidable technical challenges, because smartphones lack the huge computing resources and energy available in a data center. Solving this problem could mean that AI assistants respond more quickly than they do from the cloud and even work offline.

Ensuring that queries are answered on an individual’s own device without sending data to the cloud is also likely to bring privacy benefits, a key differentiator for Apple in recent years.

“Our experiment is designed to optimize inference efficiency on personal devices,” its researchers said. Apple tested its approach on models including Falcon 7B, a smaller version of an open source LLM originally developed by the Technology Innovation Institute in Abu Dhabi.

Optimizing LLMs to run on battery-powered devices has been a growing focus for AI researchers. Academic papers are not a direct indicator of how Apple intends to add new features to its products, but they offer a rare glimpse into its secretive research labs and the company’s latest technical breakthroughs.

“Our work not only provides a solution to a current computational bottleneck but also sets a precedent for future research,” wrote Apple’s researchers in the conclusion to their paper. “We believe as LLMs continue to grow in size and complexity, approaches like this work will be essential for harnessing their full potential in a wide range of devices and applications.”

Apple did not immediately respond to a request for comment.

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