AI

openai-experiments-with-giving-chatgpt-a-long-term-conversation-memory

OpenAI experiments with giving ChatGPT a long-term conversation memory

“I remember…the Alamo” —

AI chatbot “memory” will recall facts from previous conversations when enabled.

A pixelated green illustration of a pair of hands looking through file records.

Enlarge / When ChatGPT looks things up, a pair of green pixelated hands look through paper records, much like this. Just kidding.

Benj Edwards / Getty Images

On Tuesday, OpenAI announced that it is experimenting with adding a form of long-term memory to ChatGPT that will allow it to remember details between conversations. You can ask ChatGPT to remember something, see what it remembers, and ask it to forget. Currently, it’s only available to a small number of ChatGPT users for testing.

So far, large language models have typically used two types of memory: one baked into the AI model during the training process (before deployment) and an in-context memory (the conversation history) that persists for the duration of your session. Usually, ChatGPT forgets what you have told it during a conversation once you start a new session.

Various projects have experimented with giving LLMs a memory that persists beyond a context window. (The context window is the hard limit on the number of tokens the LLM can process at once.) The techniques include dynamically managing context history, compressing previous history through summarization, links to vector databases that store information externally, or simply periodically injecting information into a system prompt (the instructions ChatGPT receives at the beginning of every chat).

A screenshot of ChatGPT memory controls provided by OpenAI.

Enlarge / A screenshot of ChatGPT memory controls provided by OpenAI.

OpenAI

OpenAI hasn’t explained which technique it uses here, but the implementation reminds us of Custom Instructions, a feature OpenAI introduced in July 2023 that lets users add custom additions to the ChatGPT system prompt to change its behavior.

Possible applications for the memory feature provided by OpenAI include explaining how you prefer your meeting notes to be formatted, telling it you run a coffee shop and having ChatGPT assume that’s what you’re talking about, keeping information about your toddler that loves jellyfish so it can generate relevant graphics, and remembering preferences for kindergarten lesson plan designs.

Also, OpenAI says that memories may help ChatGPT Enterprise and Team subscribers work together better since shared team memories could remember specific document formatting preferences or which programming frameworks your team uses. And OpenAI plans to bring memories to GPTs soon, with each GPT having its own siloed memory capabilities.

Memory control

Obviously, any tendency to remember information brings privacy implications. You should already know that sending information to OpenAI for processing on remote servers introduces the possibility of privacy leaks and that OpenAI trains AI models on user-provided information by default unless conversation history is disabled or you’re using an Enterprise or Team account.

Along those lines, OpenAI says that your saved memories are also subject to OpenAI training use unless you meet the criteria listed above. Still, the memory feature can be turned off completely. Additionally, the company says, “We’re taking steps to assess and mitigate biases, and steer ChatGPT away from proactively remembering sensitive information, like your health details—unless you explicitly ask it to.”

Users will also be able to control what ChatGPT remembers using a “Manage Memory” interface that lists memory items. “ChatGPT’s memories evolve with your interactions and aren’t linked to specific conversations,” OpenAI says. “Deleting a chat doesn’t erase its memories; you must delete the memory itself.”

ChatGPT’s memory features are not currently available to every ChatGPT account, so we have not experimented with it yet. Access during this testing period appears to be random among ChatGPT (free and paid) accounts for now. “We are rolling out to a small portion of ChatGPT free and Plus users this week to learn how useful it is,” OpenAI writes. “We will share plans for broader roll out soon.”

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judge-rejects-most-chatgpt-copyright-claims-from-book-authors

Judge rejects most ChatGPT copyright claims from book authors

Insufficient evidence —

OpenAI plans to defeat authors’ remaining claim at a “later stage” of the case.

Judge rejects most ChatGPT copyright claims from book authors

A US district judge in California has largely sided with OpenAI, dismissing the majority of claims raised by authors alleging that large language models powering ChatGPT were illegally trained on pirated copies of their books without their permission.

By allegedly repackaging original works as ChatGPT outputs, authors alleged, OpenAI’s most popular chatbot was just a high-tech “grift” that seemingly violated copyright laws, as well as state laws preventing unfair business practices and unjust enrichment.

According to judge Araceli Martínez-Olguín, authors behind three separate lawsuits—including Sarah Silverman, Michael Chabon, and Paul Tremblay—have failed to provide evidence supporting any of their claims except for direct copyright infringement.

OpenAI had argued as much in their promptly filed motion to dismiss these cases last August. At that time, OpenAI said that it expected to beat the direct infringement claim at a “later stage” of the proceedings.

Among copyright claims tossed by Martínez-Olguín were accusations of vicarious copyright infringement. Perhaps most significantly, Martínez-Olguín agreed with OpenAI that the authors’ allegation that “every” ChatGPT output “is an infringing derivative work” is “insufficient” to allege vicarious infringement, which requires evidence that ChatGPT outputs are “substantially similar” or “similar at all” to authors’ books.

“Plaintiffs here have not alleged that the ChatGPT outputs contain direct copies of the copyrighted books,” Martínez-Olguín wrote. “Because they fail to allege direct copying, they must show a substantial similarity between the outputs and the copyrighted materials.”

Authors also failed to convince Martínez-Olguín that OpenAI violated the Digital Millennium Copyright Act (DMCA) by allegedly removing copyright management information (CMI)—such as author names, titles of works, and terms and conditions for use of the work—from training data.

This claim failed because authors cited “no facts” that OpenAI intentionally removed the CMI or built the training process to omit CMI, Martínez-Olguín wrote. Further, the authors cited examples of ChatGPT referencing their names, which would seem to suggest that some CMI remains in the training data.

Some of the remaining claims were dependent on copyright claims to survive, Martínez-Olguín wrote.

Arguing that OpenAI caused economic injury by unfairly repurposing authors’ works, even if authors could show evidence of a DMCA violation, authors could only speculate about what injury was caused, the judge said.

Similarly, allegations of “fraudulent” unfair conduct—accusing OpenAI of “deceptively” designing ChatGPT to produce outputs that omit CMI—”rest on a violation of the DMCA,” Martínez-Olguín wrote.

The only claim under California’s unfair competition law that was allowed to proceed alleged that OpenAI used copyrighted works to train ChatGPT without authors’ permission. Because the state law broadly defines what’s considered “unfair,” Martínez-Olguín said that it’s possible that OpenAI’s use of the training data “may constitute an unfair practice.”

Remaining claims of negligence and unjust enrichment failed, Martínez-Olguín wrote, because authors only alleged intentional acts and did not explain how OpenAI “received and unjustly retained a benefit” from training ChatGPT on their works.

Authors have been ordered to consolidate their complaints and have until March 13 to amend arguments and continue pursuing any of the dismissed claims.

To shore up the tossed copyright claims, authors would likely need to provide examples of ChatGPT outputs that are similar to their works, as well as evidence of OpenAI intentionally removing CMI to “induce, enable, facilitate, or conceal infringement,” Martínez-Olguín wrote.

Ars could not immediately reach the authors’ lawyers or OpenAI for comment.

As authors likely prepare to continue fighting OpenAI, the US Copyright Office has been fielding public input before releasing guidance that could one day help rights holders pursue legal claims and may eventually require works to be licensed from copyright owners for use as training materials. Among the thorniest questions is whether AI tools like ChatGPT should be considered authors when spouting outputs included in creative works.

While the Copyright Office prepares to release three reports this year “revealing its position on copyright law in relation to AI,” according to The New York Times, OpenAI recently made it clear that it does not plan to stop referencing copyrighted works in its training data. Last month, OpenAI said it would be “impossible” to train AI models without copyrighted materials, because “copyright today covers virtually every sort of human expression—including blogposts, photographs, forum posts, scraps of software code, and government documents.”

According to OpenAI, it doesn’t just need old copyrighted materials; it needs current copyright materials to ensure that chatbot and other AI tools’ outputs “meet the needs of today’s citizens.”

Rights holders will likely be bracing throughout this confusing time, waiting for the Copyright Office’s reports. But once there is clarity, those reports could “be hugely consequential, weighing heavily in courts, as well as with lawmakers and regulators,” The Times reported.

Judge rejects most ChatGPT copyright claims from book authors Read More »

the-super-bowl’s-best-and-wackiest-ai-commercials

The Super Bowl’s best and wackiest AI commercials

Superb Owl News —

It’s nothing like “crypto bowl” in 2022, but AI made a notable splash during the big game.

A still image from BodyArmor's 2024

Enlarge / A still image from BodyArmor’s 2024 “Field of Fake” Super Bowl commercial.

BodyArmor

Heavily hyped tech products have a history of appearing in Super Bowl commercials during football’s biggest game—including the Apple Macintosh in 1984, dot-com companies in 2000, and cryptocurrency firms in 2022. In 2024, the hot tech in town is artificial intelligence, and several companies showed AI-related ads at Super Bowl LVIII. Here’s a rundown of notable appearances that range from serious to wacky.

Microsoft Copilot

Microsoft Game Day Commercial | Copilot: Your everyday AI companion.

It’s been a year since Microsoft launched the AI assistant Microsoft Copilot (as “Bing Chat“), and Microsoft is leaning heavily into its AI-assistant technology, which is powered by large language models from OpenAI. In Copilot’s first-ever Super Bowl commercial, we see scenes of various people with defiant text overlaid on the screen: “They say I will never open my own business or get my degree. They say I will never make my movie or build something. They say I’m too old to learn something new. Too young to change the world. But I say watch me.”

Then the commercial shows Copilot creating solutions to some of these problems, with prompts like, “Generate storyboard images for the dragon scene in my script,” “Write code for my 3d open world game,” “Quiz me in organic chemistry,” and “Design a sign for my classic truck repair garage Mike’s.”

Of course, since generative AI is an unfinished technology, many of these solutions are more aspirational than practical at the moment. On Bluesky, writer Ed Zitron put Microsoft’s truck repair logo to the test and saw results that weren’t nearly as polished as those seen in the commercial. On X, others have criticized and poked fun at the “3d open world game” generation prompt, which is a complex task that would take far more than a single, simple prompt to produce useful code.

Google Pixel 8 “Guided Frame” feature

Javier in Frame | Google Pixel SB Commercial 2024.

Instead of focusing on generative aspects of AI, Google’s commercial showed off a feature called “Guided Frame” on the Pixel 8 phone that uses machine vision technology and a computer voice to help people with blindness or low vision to take photos by centering the frame on a face or multiple faces. Guided Frame debuted in 2022 in conjunction with the Google Pixel 7.

The commercial tells the story of a person named Javier, who says, “For many people with blindness or low vision, there hasn’t always been an easy way to capture daily life.” We see a simulated blurry first-person view of Javier holding a smartphone and hear a computer-synthesized voice describing what the AI model sees, directing the person to center on a face to snap various photos and selfies.

Considering the controversies that generative AI currently generates (pun intended), it’s refreshing to see a positive application of AI technology used as an accessibility feature. Relatedly, an app called Be My Eyes (powered by OpenAI’s GPT-4V) also aims to help low-vision people interact with the world.

Despicable Me 4

Despicable Me 4 – Minion Intelligence (Big Game Spot).

So far, we’ve covered a couple attempts to show AI-powered products as positive features. Elsewhere in Super Bowl ads, companies weren’t as generous about the technology. In an ad for the film Despicable Me 4, we see two Minions creating a series of terribly disfigured AI-generated still images reminiscent of Stable Diffusion 1.4 from 2022. There’s three-legged people doing yoga, a painting of Steve Carell and Will Ferrell as Elizabethan gentlemen, a handshake with too many fingers, people eating spaghetti in a weird way, and a pair of people riding dachshunds in a race.

The images are paired with an earnest voiceover that says, “Artificial intelligence is changing the way we see the world, showing us what we never thought possible, transforming the way we do business, and bringing family and friends closer together. With artificial intelligence, the future is in good hands.” When the voiceover ends, the camera pans out to show hundreds of Minions generating similarly twisted images on computers.

Speaking of image synthesis at the Super Bowl, people mistook a Christian commercial created by He Gets Us, LLC as having been AI-generated, likely due to its gaudy technicolor visuals. With the benefit of a YouTube replay and the ability to look at details, the “He washed feet” commercial doesn’t appear AI-generated to us, but it goes to show how the concept of image synthesis has begun to cast doubt on human-made creations.

The Super Bowl’s best and wackiest AI commercials Read More »

london-underground-is-testing-real-time-ai-surveillance-tools-to-spot-crime

London Underground is testing real-time AI surveillance tools to spot crime

tube tracking —

Computer vision system tried to detect crime, weapons, people falling, and fare dodgers.

Commuters wait on the platform as a Central Line tube train arrives at Liverpool Street London Transport Tube Station in 2023.

Thousands of people using the London Underground had their movements, behavior, and body language watched by AI surveillance software designed to see if they were committing crimes or were in unsafe situations, new documents obtained by WIRED reveal. The machine-learning software was combined with live CCTV footage to try to detect aggressive behavior and guns or knives being brandished, as well as looking for people falling onto Tube tracks or dodging fares.

From October 2022 until the end of September 2023, Transport for London (TfL), which operates the city’s Tube and bus network, tested 11 algorithms to monitor people passing through Willesden Green Tube station, in the northwest of the city. The proof of concept trial is the first time the transport body has combined AI and live video footage to generate alerts that are sent to frontline staff. More than 44,000 alerts were issued during the test, with 19,000 being delivered to station staff in real time.

Documents sent to WIRED in response to a Freedom of Information Act request detail how TfL used a wide range of computer vision algorithms to track people’s behavior while they were at the station. It is the first time the full details of the trial have been reported, and it follows TfL saying, in December, that it will expand its use of AI to detect fare dodging to more stations across the British capital.

In the trial at Willesden Green—a station that had 25,000 visitors per day before the COVID-19 pandemic—the AI system was set up to detect potential safety incidents to allow staff to help people in need, but it also targeted criminal and antisocial behavior. Three documents provided to WIRED detail how AI models were used to detect wheelchairs, prams, vaping, people accessing unauthorized areas, or putting themselves in danger by getting close to the edge of the train platforms.

The documents, which are partially redacted, also show how the AI made errors during the trial, such as flagging children who were following their parents through ticket barriers as potential fare dodgers, or not being able to tell the difference between a folding bike and a non-folding bike. Police officers also assisted the trial by holding a machete and a gun in the view of CCTV cameras, while the station was closed, to help the system better detect weapons.

Privacy experts who reviewed the documents question the accuracy of object detection algorithms. They also say it is not clear how many people knew about the trial, and warn that such surveillance systems could easily be expanded in the future to include more sophisticated detection systems or face recognition software that attempts to identify specific individuals. “While this trial did not involve facial recognition, the use of AI in a public space to identify behaviors, analyze body language, and infer protected characteristics raises many of the same scientific, ethical, legal, and societal questions raised by facial recognition technologies,” says Michael Birtwistle, associate director at the independent research institute the Ada Lovelace Institute.

In response to WIRED’s Freedom of Information request, the TfL says it used existing CCTV images, AI algorithms, and “numerous detection models” to detect patterns of behavior. “By providing station staff with insights and notifications on customer movement and behaviour they will hopefully be able to respond to any situations more quickly,” the response says. It also says the trial has provided insight into fare evasion that will “assist us in our future approaches and interventions,” and the data gathered is in line with its data policies.

In a statement sent after publication of this article, Mandy McGregor, TfL’s head of policy and community safety, says the trial results are continuing to be analyzed and adds, “there was no evidence of bias” in the data collected from the trial. During the trial, McGregor says, there were no signs in place at the station that mentioned the tests of AI surveillance tools.

“We are currently considering the design and scope of a second phase of the trial. No other decisions have been taken about expanding the use of this technology, either to further stations or adding capability.” McGregor says. “Any wider roll out of the technology beyond a pilot would be dependent on a full consultation with local communities and other relevant stakeholders, including experts in the field.”

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report:-sam-altman-seeking-trillions-for-ai-chip-fabrication-from-uae,-others

Report: Sam Altman seeking trillions for AI chip fabrication from UAE, others

chips ahoy —

WSJ: Audacious $5-$7 trillion investment would aim to expand global AI chip supply.

WASHINGTON, DC - JANUARY 11: OpenAI Chief Executive Officer Sam Altman walks on the House side of the U.S. Capitol on January 11, 2024 in Washington, DC. Meanwhile, House Freedom Caucus members who left a meeting in the Speakers office say that they were talking to the Speaker about abandoning the spending agreement that Johnson announced earlier in the week. (Photo by Kent Nishimura/Getty Images)

Enlarge / OpenAI Chief Executive Officer Sam Altman walks on the House side of the US Capitol on January 11, 2024, in Washington, DC. (Photo by Kent Nishimura/Getty Images)

Getty Images

On Thursday, The Wall Street Journal reported that OpenAI CEO Sam Altman is in talks with investors to raise as much as $5 trillion to $7 trillion for AI chip manufacturing, according to people familiar with the matter. The funding seeks to address the scarcity of graphics processing units (GPUs) crucial for training and running large language models like those that power ChatGPT, Microsoft Copilot, and Google Gemini.

The high dollar amount reflects the huge amount of capital necessary to spin up new semiconductor manufacturing capability. “As part of the talks, Altman is pitching a partnership between OpenAI, various investors, chip makers and power providers, which together would put up money to build chip foundries that would then be run by existing chip makers,” writes the Wall Street Journal in its report. “OpenAI would agree to be a significant customer of the new factories.”

To hit these ambitious targets—which are larger than the entire semiconductor industry’s current $527 billion global sales combined—Altman has reportedly met with a range of potential investors worldwide, including sovereign wealth funds and government entities, notably the United Arab Emirates, SoftBank CEO Masayoshi Son, and representatives from Taiwan Semiconductor Manufacturing Co. (TSMC).

TSMC is the world’s largest dedicated independent semiconductor foundry. It’s a critical linchpin that companies such as Nvidia, Apple, Intel, and AMD rely on to fabricate SoCs, CPUs, and GPUs for various applications.

Altman reportedly seeks to expand the global capacity for semiconductor manufacturing significantly, funding the infrastructure necessary to support the growing demand for GPUs and other AI-specific chips. GPUs are excellent at parallel computation, which makes them ideal for running AI models that heavily rely on matrix multiplication to work. However, the technology sector currently faces a significant shortage of these important components, constraining the potential for AI advancements and applications.

In particular, the UAE’s involvement, led by Sheikh Tahnoun bin Zayed al Nahyan, a key security official and chair of numerous Abu Dhabi sovereign wealth vehicles, reflects global interest in AI’s potential and the strategic importance of semiconductor manufacturing. However, the prospect of substantial UAE investment in a key tech industry raises potential geopolitical concerns, particularly regarding the US government’s strategic priorities in semiconductor production and AI development.

The US has been cautious about allowing foreign control over the supply of microchips, given their importance to the digital economy and national security. Reflecting this, the Biden administration has undertaken efforts to bolster domestic chip manufacturing through subsidies and regulatory scrutiny of foreign investments in important technologies.

To put the $5 trillion to $7 trillion estimate in perspective, the White House just today announced a $5 billion investment in R&D to advance US-made semiconductor technologies. TSMC has already sunk $40 billion—one of the largest foreign investments in US history—into a US chip plant in Arizona. As of now, it’s unclear whether Altman has secured any commitments toward his fundraising goal.

Updated on February 9, 2024 at 8: 45 PM Eastern with a quote from the WSJ that clarifies the proposed relationship between OpenAI and partners in the talks.

Report: Sam Altman seeking trillions for AI chip fabrication from UAE, others Read More »

ai-cannot-be-used-to-deny-health-care-coverage,-feds-clarify-to-insurers

AI cannot be used to deny health care coverage, feds clarify to insurers

On Notice —

CMS worries AI could wrongfully deny care for those on Medicare Advantage plans.

A nursing home resident is pushed along a corridor by a nurse.

Enlarge / A nursing home resident is pushed along a corridor by a nurse.

Health insurance companies cannot use algorithms or artificial intelligence to determine care or deny coverage to members on Medicare Advantage plans, the Centers for Medicare & Medicaid Services (CMS) clarified in a memo sent to all Medicare Advantage insurers.

The memo—formatted like an FAQ on Medicare Advantage (MA) plan rules—comes just months after patients filed lawsuits claiming that UnitedHealth and Humana have been using a deeply flawed, AI-powered tool to deny care to elderly patients on MA plans. The lawsuits, which seek class-action status, center on the same AI tool, called nH Predict, used by both insurers and developed by NaviHealth, a UnitedHealth subsidiary.

According to the lawsuits, nH Predict produces draconian estimates for how long a patient will need post-acute care in facilities like skilled nursing homes and rehabilitation centers after an acute injury, illness, or event, like a fall or a stroke. And NaviHealth employees face discipline for deviating from the estimates, even though they often don’t match prescribing physicians’ recommendations or Medicare coverage rules. For instance, while MA plans typically provide up to 100 days of covered care in a nursing home after a three-day hospital stay, using nH Predict, patients on UnitedHealth’s MA plan rarely stay in nursing homes for more than 14 days before receiving payment denials, the lawsuits allege.

Specific warning

It’s unclear how nH Predict works exactly, but it reportedly uses a database of 6 million patients to develop its predictions. Still, according to people familiar with the software, it only accounts for a small set of patient factors, not a full look at a patient’s individual circumstances.

This is a clear no-no, according to the CMS’s memo. For coverage decisions, insurers must “base the decision on the individual patient’s circumstances, so an algorithm that determines coverage based on a larger data set instead of the individual patient’s medical history, the physician’s recommendations, or clinical notes would not be compliant,” the CMS wrote.

The CMS then provided a hypothetical that matches the circumstances laid out in the lawsuits, writing:

In an example involving a decision to terminate post-acute care services, an algorithm or software tool can be used to assist providers or MA plans in predicting a potential length of stay, but that prediction alone cannot be used as the basis to terminate post-acute care services.

Instead, the CMS wrote, in order for an insurer to end coverage, the individual patient’s condition must be reassessed, and denial must be based on coverage criteria that is publicly posted on a website that is not password protected. In addition, insurers who deny care “must supply a specific and detailed explanation why services are either no longer reasonable and necessary or are no longer covered, including a description of the applicable coverage criteria and rules.”

In the lawsuits, patients claimed that when coverage of their physician-recommended care was unexpectedly wrongfully denied, insurers didn’t give them full explanations.

Fidelity

In all, the CMS finds that AI tools can be used by insurers when evaluating coverage—but really only as a check to make sure the insurer is following the rules. An “algorithm or software tool should only be used to ensure fidelity,” with coverage criteria, the CMS wrote. And, because “publicly posted coverage criteria are static and unchanging, artificial intelligence cannot be used to shift the coverage criteria over time” or apply hidden coverage criteria.

The CMS sidesteps any debate about what qualifies as artificial intelligence by offering a broad warning about algorithms and artificial intelligence. “There are many overlapping terms used in the context of rapidly developing software tools,” the CMS wrote.

Algorithms can imply a decisional flow chart of a series of if-then statements (i.e., if the patient has a certain diagnosis, they should be able to receive a test), as well as predictive algorithms (predicting the likelihood of a future admission, for example). Artificial intelligence has been defined as a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. Artificial intelligence systems use machine- and human-based inputs to perceive real and virtual environments; abstract such perceptions into models through analysis in an automated manner; and use model inference to formulate options for information or action.

The CMS also openly worried that the use of either of these types of tools can reinforce discrimination and biases—which has already happened with racial bias. The CMS warned insurers to ensure any AI tool or algorithm they use “is not perpetuating or exacerbating existing bias, or introducing new biases.”

While the memo overall was an explicit clarification of existing MA rules, the CMS ended by putting insurers on notice that it is increasing its audit activities and “will be monitoring closely whether MA plans are utilizing and applying internal coverage criteria that are not found in Medicare laws.” Non-compliance can result in warning letters, corrective action plans, monetary penalties, and enrollment and marketing sanctions.

AI cannot be used to deny health care coverage, feds clarify to insurers Read More »

your-current-pc-probably-doesn’t-have-an-ai-processor,-but-your-next-one-might

Your current PC probably doesn’t have an AI processor, but your next one might

Intel's Core Ultra chips are some of the first x86 PC processors to include built-in NPUs. Software support will slowly follow.

Enlarge / Intel’s Core Ultra chips are some of the first x86 PC processors to include built-in NPUs. Software support will slowly follow.

Intel

When it announced the new Copilot key for PC keyboards last month, Microsoft declared 2024 “the year of the AI PC.” On one level, this is just an aspirational PR-friendly proclamation, meant to show investors that Microsoft intends to keep pushing the AI hype cycle that has put it in competition with Apple for the title of most valuable publicly traded company.

But on a technical level, it is true that PCs made and sold in 2024 and beyond will generally include AI and machine-learning processing capabilities that older PCs don’t. The main thing is the neural processing unit (NPU), a specialized block on recent high-end Intel and AMD CPUs that can accelerate some kinds of generative AI and machine-learning workloads more quickly (or while using less power) than the CPU or GPU could.

Qualcomm’s Windows PCs were some of the first to include an NPU, since the Arm processors used in most smartphones have included some kind of machine-learning acceleration for a few years now (Apple’s M-series chips for Macs all have them, too, going all the way back to 2020’s M1). But the Arm version of Windows is a insignificantly tiny sliver of the entire PC market; x86 PCs with Intel’s Core Ultra chips, AMD’s Ryzen 7040/8040-series laptop CPUs, or the Ryzen 8000G desktop CPUs will be many mainstream PC users’ first exposure to this kind of hardware.

Right now, even if your PC has an NPU in it, Windows can’t use it for much, aside from webcam background blurring and a handful of other video effects. But that’s slowly going to change, and part of that will be making it relatively easy for developers to create NPU-agnostic apps in the same way that PC game developers currently make GPU-agnostic games.

The gaming example is instructive, because that’s basically how Microsoft is approaching DirectML, its API for machine-learning operations. Though up until now it has mostly been used to run these AI workloads on GPUs, Microsoft announced last week that it was adding DirectML support for Intel’s Meteor Lake NPUs in a developer preview, starting in DirectML 1.13.1 and ONNX Runtime 1.17.

Though it will only run an unspecified “subset of machine learning models that have been targeted for support” and that some “may not run at all or may have high latency or low accuracy,” it opens the door to more third-party apps to start taking advantage of built-in NPUs. Intel says that Samsung is using Intel’s NPU and DirectML for facial recognition features in its photo gallery app, something that Apple also uses its Neural Engine for in macOS and iOS.

The benefits can be substantial, compared to running those workloads on a GPU or CPU.

“The NPU, at least in Intel land, will largely be used for power efficiency reasons,” Intel Senior Director of Technical Marketing Robert Hallock told Ars in an interview about Meteor Lake’s capabilities. “Camera segmentation, this whole background blurring thing… moving that to the NPU saves about 30 to 50 percent power versus running it elsewhere.”

Intel and Microsoft are both working toward a model where NPUs are treated pretty much like GPUs are today: developers generally target DirectX rather than a specific graphics card manufacturer or GPU architecture, and new features, one-off bug fixes, and performance improvements can all be addressed via GPU driver updates. Some GPUs run specific games better than others, and developers can choose to spend more time optimizing for Nvidia cards or AMD cards, but generally the model is hardware agnostic.

Similarly, Intel is already offering GPU-style driver updates for its NPUs. And Hallock says that Windows already essentially recognizes the NPU as “a graphics card with no rendering capability.”

Your current PC probably doesn’t have an AI processor, but your next one might Read More »

microsoft-in-deal-with-semafor-to-create-news-stories-with-aid-of-ai-chatbot

Microsoft in deal with Semafor to create news stories with aid of AI chatbot

a meeting-deadline helper —

Collaboration comes as tech giant faces multibillion-dollar lawsuit from The New York Times.

Cube with Microsoft logo on top of their office building on 8th Avenue and 42nd Street near Times Square in New York City.

Enlarge / Cube with Microsoft logo on top of their office building on 8th Avenue and 42nd Street near Times Square in New York City.

Microsoft is working with media startup Semafor to use its artificial intelligence chatbot to help develop news stories—part of a journalistic outreach that comes as the tech giant faces a multibillion-dollar lawsuit from the New York Times.

As part of the agreement, Microsoft is paying an undisclosed sum of money to Semafor to sponsor a breaking news feed called “Signals.” The companies would not share financial details, but the amount of money is “substantial” to Semafor’s business, said a person familiar with the matter.

Signals will offer a feed of breaking news and analysis on big stories, with about a dozen posts a day. The goal is to offer different points of view from across the globe—a key focus for Semafor since its launch in 2022.

Semafor co-founder Ben Smith emphasized that Signals will be written entirely by journalists, with artificial intelligence providing a research tool to inform posts.

Microsoft on Monday was also set to announce collaborations with journalist organizations including the Craig Newmark School of Journalism, the Online News Association, and the GroundTruth Project.

The partnerships come as media companies have become increasingly concerned over generative AI and its potential threat to their businesses. News publishers are grappling with how to use AI to improve their work and stay ahead of technology, while also fearing that they could lose traffic, and therefore revenue, to AI chatbots—which can churn out humanlike text and information in seconds.

The New York Times in December filed a lawsuit against Microsoft and OpenAI, alleging the tech companies have taken a “free ride” on millions of its articles to build their artificial intelligence chatbots, and seeking billions of dollars in damages.

Gina Chua, Semafor’s executive editor, has been involved in developing Semafor’s AI research tools, which are powered by ChatGPT and Microsoft’s Bing.

“Journalism has always used technology whether it’s carrier pigeons, the telegraph or anything else . . . this represents a real opportunity, a set of tools that are really a quantum leap above many of the other tools that have come along,” Chua said.

For a breaking news event, Semafor journalists will use AI tools to quickly search for reporting and commentary from other news sources across the globe in multiple languages. A Signals post might include perspectives from Chinese, Indian, or Russian media, for example, with Semafor’s reporters summarizing and contextualizing the different points of view, while citing its sources.

Noreen Gillespie, a former Associated Press journalist, joined Microsoft three months ago to forge relationships with news companies. “Journalists need to adopt these tools in order to survive and thrive for another generation,” she said.

Semafor was founded by Ben Smith, the former BuzzFeed editor, and Justin Smith, the former chief executive of Bloomberg Media.

Semafor, which is free to read, is funded by wealthy individuals, including 3G capital founder Jorge Paulo Lemann and KKR co-founder Henry Kravis. The company made more than $10 million in revenue in 2023 and has more than 500,000 subscriptions to its free newsletters. Justin Smith said Semafor was “very close to a profit” in the fourth quarter of 2023.

“What we’re trying to go after is this really weird space of breaking news on the Internet now, in which you have these really splintered, fragmented, rushed efforts to get the first sentence of a story out for search engines . . . and then never really make any effort to provide context,” Ben Smith said.

“We’re trying to go the other way. Here are the confirmed facts. Here are three or four pieces of really sophisticated, meaningful analysis.”

© 2024 The Financial Times Ltd. All rights reserved. Please do not copy and paste FT articles and redistribute by email or post to the web.

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chatgpt’s-new-@-mentions-bring-multiple-personalities-into-your-ai-convo

ChatGPT’s new @-mentions bring multiple personalities into your AI convo

team of rivals —

Bring different AI roles into the same chatbot conversation history.

Illustration of a man jugging at symbols.

Enlarge / With so many choices, selecting the perfect GPT can be confusing.

On Tuesday, OpenAI announced a new feature in ChatGPT that allows users to pull custom personalities called “GPTs” into any ChatGPT conversation with the @ symbol. It allows a level of quasi-teamwork within ChatGPT among expert roles that was previously impractical, making collaborating with a team of AI agents within OpenAI’s platform one step closer to reality.

You can now bring GPTs into any conversation in ChatGPT – simply type @ and select the GPT,” wrote OpenAI on the social media network X. “This allows you to add relevant GPTs with the full context of the conversation.”

OpenAI introduced GPTs in November as a way to create custom personalities or roles for ChatGPT to play. For example, users can build their own GPTs to focus on certain topics or certain skills. Paid ChatGPT subscribers can also freely download a host of GPTs developed by other ChatGPT users through the GPT Store.

Previously, if you wanted to share information between GPT profiles, you had to copy the text, select a new chat with the GPT, paste it, and explain the context of what the information means or what you want to do with it. Now, ChatGPT users can stay in the default ChatGPT window and bring in GPTs as needed without losing the history of the conversation.

For example, we created a “Wellness Guide” GPT that is crafted as an expert in human health conditions (of course, this being ChatGPT, always consult a human doctor if you’re having medical problems), and we created a “Canine Health Advisor” for dog-related health questions.

A screenshot of ChatGPT where we @-mentioned a human wellness advisor, then a dog advisor in the same conversation history.

Enlarge / A screenshot of ChatGPT where we @-mentioned a human wellness advisor, then a dog advisor in the same conversation history.

Benj Edwards

We started in a default ChatGPT chat, hit the @ symbol, then typed the first few letters of “Wellness” and selected it from a list. It filled out the rest. We asked a question about food poisoning in humans, and then we switched to the canine advisor in the same way with an @ symbol and asked about the dog.

Using this feature, you could alternatively consult, say, an “ad copywriter” GPT and an “editor” GPT—ask the copywriter to write some text, then rope in the editor GPT to check it, looking at it from a different angle. Different system prompts (the instructions that define a GPT’s personality) make for significant behavior differences.

We also tried swapping between GPT profiles that write software and others designed to consult on historical tech subjects. Interestingly, ChatGPT does not differentiate between GPTs as different personalities as you change. It will still say, “I did this earlier” when a different GPT is talking about a previous GPT’s output in the same conversation history. From its point of view, it’s just ChatGPT and not multiple agents.

From our vantage point, this feature seems to represent baby steps toward a future where GPTs, as independent agents, could work together as a team to fulfill more complex tasks directed by the user. Similar experiments have been done outside of OpenAI in the past (using API access), but OpenAI has so far resisted a more agentic model for ChatGPT. As we’ve seen (first with GPTs and now with this), OpenAI seems to be slowly angling toward that goal itself, but only time will tell if or when we see true agentic teamwork in a shipping service.

ChatGPT’s new @-mentions bring multiple personalities into your AI convo Read More »

rhyming-ai-powered-clock-sometimes-lies-about-the-time,-makes-up-words

Rhyming AI-powered clock sometimes lies about the time, makes up words

Confabulation time —

Poem/1 Kickstarter seeks $103K for fun ChatGPT-fed clock that may hallucinate the time.

A CAD render of the Poem/1 sitting on a bookshelf.

Enlarge / A CAD render of the Poem/1 sitting on a bookshelf.

On Tuesday, product developer Matt Webb launched a Kickstarter funding project for a whimsical e-paper clock called the “Poem/1” that tells the current time using AI and rhyming poetry. It’s powered by the ChatGPT API, and Webb says that sometimes ChatGPT will lie about the time or make up words to make the rhymes work.

“Hey so I made a clock. It tells the time with a brand new poem every minute, composed by ChatGPT. It’s sometimes profound, and sometimes weird, and occasionally it fibs about what the actual time is to make a rhyme work,” Webb writes on his Kickstarter page.

The $126 clock is the product of Webb’s Acts Not Facts, which he bills as “.” Despite the net-connected service aspect of the clock, Webb says it will not require a subscription to function.

A labeled CAD rendering of the Poem/1 clock, representing its final shipping configuration.

Enlarge / A labeled CAD rendering of the Poem/1 clock, representing its final shipping configuration.

There are 1,440 minutes in a day, so Poem/1 needs to display 1,440 unique poems to work. The clock features a monochrome e-paper screen and pulls its poetry rhymes via Wi-Fi from a central server run by Webb’s company. To save money, that server pulls poems from ChatGPT’s API and will share them out to many Poem/1 clocks at once. This prevents costly API fees that would add up if your clock were querying OpenAI’s servers 1,440 times a day, non-stop, forever. “I’m reserving a % of the retail price from each clock in a bank account to cover AI and server costs for 5 years,” Webb writes.

For hackers, Webb says that you’ll be able to change the back-end server URL of the Poem/1 from the default to whatever you want, so it can display custom text every minute of the day. Webb says he will document and publish the API when Poem/1 ships.

Hallucination time

A photo of a Poem/1 prototype with a hallucinated time, according to Webb.

Enlarge / A photo of a Poem/1 prototype with a hallucinated time, according to Webb.

Given the Poem/1’s large language model pedigree, it’s perhaps not surprising that Poem/1 may sometimes make up things (also called “hallucination” or “confabulation” in the AI field) to fulfill its task. The LLM that powers ChatGPT is always searching for the most likely next word in a sequence, and sometimes factuality comes second to fulfilling that mission.

Further down on the Kickstarter page, Webb provides a photo of his prototype Poem/1 where the screen reads, “As the clock strikes eleven forty two, / I rhyme the time, as I always do.” Just below, Webb warns, “Poem/1 fibs occasionally. I don’t believe it was actually 11.42 when this photo was taken. The AI hallucinated the time in order to make the poem work. What we do for art…”

In other clocks, the tendency to unreliably tell the time might be a fatal flaw. But judging by his humorous angle on the Kickstarter page, Webb apparently sees the clock as more of a fun art project than a precision timekeeping instrument. “Don’t rely on this clock in situations where timekeeping is vital,” Webb writes, “such as if you work in air traffic control or rocket launches or the finish line of athletics competitions.”

Poem/1 also sometimes takes poetic license with vocabulary to tell the time. During a humorous moment in the Kickstarter promotional video, Webb looks at his clock prototype and reads the rhyme, “A clock that defies all rhyme and reason / 4: 30 PM, a temporal teason.” Then he says, “I had to look ‘teason’ up. It doesn’t mean anything, so it’s a made-up word.”

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chatgpt-is-leaking-passwords-from-private-conversations-of-its-users,-ars-reader-says

ChatGPT is leaking passwords from private conversations of its users, Ars reader says

OPENAI SPRINGS A LEAK —

Names of unpublished research papers, presentations, and PHP scripts also leaked.

OpenAI logo displayed on a phone screen and ChatGPT website displayed on a laptop screen.

Getty Images

ChatGPT is leaking private conversations that include login credentials and other personal details of unrelated users, screenshots submitted by an Ars reader on Monday indicated.

Two of the seven screenshots the reader submitted stood out in particular. Both contained multiple pairs of usernames and passwords that appeared to be connected to a support system used by employees of a pharmacy prescription drug portal. An employee using the AI chatbot seemed to be troubleshooting problems that encountered while using the portal.

“Horrible, horrible, horrible”

“THIS is so f-ing insane, horrible, horrible, horrible, i cannot believe how poorly this was built in the first place, and the obstruction that is being put in front of me that prevents it from getting better,” the user wrote. “I would fire [redacted name of software] just for this absurdity if it was my choice. This is wrong.”

Besides the candid language and the credentials, the leaked conversation includes the name of the app the employee is troubleshooting and the store number where the problem occurred.

The entire conversation goes well beyond what’s shown in the redacted screenshot above. A link Ars reader Chase Whiteside included showed the chat conversation in its entirety. The URL disclosed additional credential pairs.

The results appeared Monday morning shortly after reader Whiteside had used ChatGPT for an unrelated query.

“I went to make a query (in this case, help coming up with clever names for colors in a palette) and when I returned to access moments later, I noticed the additional conversations,” Whiteside wrote in an email. “They weren’t there when I used ChatGPT just last night (I’m a pretty heavy user). No queries were made—they just appeared in my history, and most certainly aren’t from me (and I don’t think they’re from the same user either).”

Other conversations leaked to Whiteside include the name of a presentation someone was working on, details of an unpublished research proposal, and a script using the PHP programming language. The users for each leaked conversation appeared to be different and unrelated to each other. The conversation involving the prescription portal included the year 2020. Dates didn’t appear in the other conversations.

The episode, and others like it, underscore the wisdom of stripping out personal details from queries made to ChatGPT and other AI services whenever possible. Last March, ChatGPT maker OpenAI took the AI chatbot offline after a bug caused the site to show titles from one active user’s chat history to unrelated users.

In November, researchers published a paper reporting how they used queries to prompt ChatGPT into divulging email addresses, phone and fax numbers, physical addresses, and other private data that was included in material used to train the ChatGPT large language model.

Concerned about the possibility of proprietary or private data leakage, companies, including Apple, have restricted their employees’ use of ChatGPT and similar sites.

As mentioned in an article from December when multiple people found that Ubiquity’s UniFy devices broadcasted private video belonging to unrelated users, these sorts of experiences are as old as the Internet is. As explained in the article:

The precise root causes of this type of system error vary from incident to incident, but they often involve “middlebox” devices, which sit between the front- and back-end devices. To improve performance, middleboxes cache certain data, including the credentials of users who have recently logged in. When mismatches occur, credentials for one account can be mapped to a different account.

An OpenAI representative said the company was investigating the report.

ChatGPT is leaking passwords from private conversations of its users, Ars reader says Read More »

openai-and-common-sense-media-partner-to-protect-teens-from-ai-harms-and-misuse

OpenAI and Common Sense Media partner to protect teens from AI harms and misuse

Adventures in chatbusting —

Site gave ChatGPT 3 stars and 48% privacy score: “Best used for creativity, not facts.”

Boy in Living Room Wearing Robot Mask

On Monday, OpenAI announced a partnership with the nonprofit Common Sense Media to create AI guidelines and educational materials targeted at parents, educators, and teens. It includes the curation of family-friendly GPTs in OpenAI’s GPT store. The collaboration aims to address concerns about the impacts of AI on children and teenagers.

Known for its reviews of films and TV shows aimed at parents seeking appropriate media for their kids to watch, Common Sense Media recently branched out into AI and has been reviewing AI assistants on its site.

“AI isn’t going anywhere, so it’s important that we help kids understand how to use it responsibly,” Common Sense Media wrote on X. “That’s why we’ve partnered with @OpenAI to help teens and families safely harness the potential of AI.”

OpenAI CEO Sam Altman and Common Sense Media CEO James Steyer announced the partnership onstage in San Francisco at the Common Sense Summit for America’s Kids and Families, an event that was well-covered by media members on the social media site X.

For his part, Altman offered a canned statement in the press release, saying, “AI offers incredible benefits for families and teens, and our partnership with Common Sense will further strengthen our safety work, ensuring that families and teens can use our tools with confidence.”

The announcement feels slightly non-specific in the official news release, with Steyer offering, “Our guides and curation will be designed to educate families and educators about safe, responsible use of ChatGPT, so that we can collectively avoid any unintended consequences of this emerging technology.”

The partnership seems aimed mostly at bringing a patina of family-friendliness to OpenAI’s GPT store, with the most solid reveal being the aforementioned fact that Common Sense media will help with the “curation of family-friendly GPTs in the GPT Store based on Common Sense ratings and standards.”

Common Sense AI reviews

As mentioned above, Common Sense Media began reviewing AI assistants on its site late last year. This puts Common Sense Media in an interesting position with potential conflicts of interest regarding the new partnership with OpenAI. However, it doesn’t seem to be offering any favoritism to OpenAI so far.

For example, Common Sense Media’s review of ChatGPT calls the AI assistant “A powerful, at times risky chatbot for people 13+ that is best used for creativity, not facts.” It labels ChatGPT as being suitable for ages 13 and up (which is in OpenAI’s Terms of Service) and gives the OpenAI assistant three out of five stars. ChatGPT also scores a 48 percent privacy rating (which is oddly shown as 55 percent on another page that goes into privacy details). The review we cited was last updated on October 13, 2023, as of this writing.

For reference, Google Bard gets a three-star overall rating and a 75 percent privacy rating in its Common Sense Media review. Stable Diffusion, the image synthesis model, nets a one-star rating with the description, “Powerful image generator can unleash creativity, but is wildly unsafe and perpetuates harm.” OpenAI’s DALL-E gets two stars and a 48 percent privacy rating.

The information that Common Sense Media includes about each AI model appears relatively accurate and detailed (and the organization cited an Ars Technica article as a reference in one explanation), so they feel fair, even in the face of the OpenAI partnership. Given the low scores, it seems that most AI models aren’t off to a great start, but that may change. It’s still early days in generative AI.

OpenAI and Common Sense Media partner to protect teens from AI harms and misuse Read More »