GPT-4 – Page 3

Mysterious “gpt2-chatbot” AI model appears suddenly, confuses experts

AI, AI benchmarks, AI vibes, Biz & IT, Chatbot Arena, Ethan Mollick, GPT-3, GPT-3.5, GPT-4, GPT-4.5, GPT-5, gpt2-chatbot, lmsys, machine learning, openai, sam altman, Simon Willison / Mike M. / May 1, 2024

Robot fortune teller hand and crystal ball

On Sunday, word began to spread on social media about a new mystery chatbot named “gpt2-chatbot” that appeared in the LMSYS Chatbot Arena. Some people speculate that it may be a secret test version of OpenAI’s upcoming GPT-4.5 or GPT-5 large language model (LLM). The paid version of ChatGPT is currently powered by GPT-4 Turbo.

Currently, the new model is only available for use through the Chatbot Arena website, although in a limited way. In the site’s “side-by-side” arena mode where users can purposely select the model, gpt2-chatbot has a rate limit of eight queries per day—dramatically limiting people’s ability to test it in detail.

So far, gpt2-chatbot has inspired plenty of rumors online, including that it could be the stealth launch of a test version of GPT-4.5 or even GPT-5—or perhaps a new version of 2019’s GPT-2 that has been trained using new techniques. We reached out to OpenAI for comment but did not receive a response by press time. On Monday evening, OpenAI CEO Sam Altman seemingly dropped a hint by tweeting, “i do have a soft spot for gpt2.”

Enlarge / A screenshot of the LMSYS Chatbot Arena “side-by-side” page showing “gpt2-chatbot” listed among the models for testing. (Red highlight added by Ars Technica.)

Benj Edwards

Early reports of the model first appeared on 4chan, then spread to social media platforms like X, with hype following not far behind. “Not only does it seem to show incredible reasoning, but it also gets notoriously challenging AI questions right with a much more impressive tone,” wrote AI developer Pietro Schirano on X. Soon, threads on Reddit popped up claiming that the new model had amazing abilities that beat every other LLM on the Arena.

Intrigued by the rumors, we decided to try out the new model for ourselves but did not come away impressed. When asked about “Benj Edwards,” the model revealed a few mistakes and some awkward language compared to GPT-4 Turbo’s output. A request for five original dad jokes fell short. And the gpt2-chatbot did not decisively pass our “magenta” test. (“Would the color be called ‘magenta’ if the town of Magenta didn’t exist?”)

A gpt2-chatbot result for “Who is Benj Edwards?” on LMSYS Chatbot Arena. Mistakes and oddities highlighted in red.

Benj Edwards
A gpt2-chatbot result for “Write 5 original dad jokes” on LMSYS Chatbot Arena.

Benj Edwards
A gpt2-chatbot result for “Would the color be called ‘magenta’ if the town of Magenta didn’t exist?” on LMSYS Chatbot Arena.

Benj Edwards

So, whatever it is, it’s probably not GPT-5. We’ve seen other people reach the same conclusion after further testing, saying that the new mystery chatbot doesn’t seem to represent a large capability leap beyond GPT-4. “Gpt2-chatbot is good. really good,” wrote HyperWrite CEO Matt Shumer on X. “But if this is gpt-4.5, I’m disappointed.”

Still, OpenAI’s fingerprints seem to be all over the new bot. “I think it may well be an OpenAI stealth preview of something,” AI researcher Simon Willison told Ars Technica. But what “gpt2” is exactly, he doesn’t know. After surveying online speculation, it seems that no one apart from its creator knows precisely what the model is, either.

Willison has uncovered the system prompt for the AI model, which claims it is based on GPT-4 and made by OpenAI. But as Willison noted in a tweet, that’s no guarantee of provenance because “the goal of a system prompt is to influence the model to behave in certain ways, not to give it truthful information about itself.”

Mysterious “gpt2-chatbot” AI model appears suddenly, confuses experts Read More »

Words are flowing out like endless rain: Recapping a busy week of LLM news

AI, Anthropic, Biz & IT, Chatbot Arena, chatgpt, chatgtp, Claude 3, Claude 3 Opus, Claude 3 Sonnet, Gemini, Gemini 1.5, Google Gemini, GPT-4, GPT-4-turbo, large language models, machine learning, Meta, Mistral, Mixtral, Mixtral 8x22B, openai, RECAP, Simon Willison, whirlwind / Kelly Newman / April 12, 2024

many things frequently —

Gemini 1.5 Pro launch, new version of GPT-4 Turbo, new Mistral model, and more.

Benj Edwards – Apr 12, 2024 8: 31 pm UTC

Enlarge / An image of a boy amazed by flying letters.

Some weeks in AI news are eerily quiet, but during others, getting a grip on the week’s events feels like trying to hold back the tide. This week has seen three notable large language model (LLM) releases: Google Gemini Pro 1.5 hit general availability with a free tier, OpenAI shipped a new version of GPT-4 Turbo, and Mistral released a new openly licensed LLM, Mixtral 8x22B. All three of those launches happened within 24 hours starting on Tuesday.

With the help of software engineer and independent AI researcher Simon Willison (who also wrote about this week’s hectic LLM launches on his own blog), we’ll briefly cover each of the three major events in roughly chronological order, then dig into some additional AI happenings this week.

Gemini Pro 1.5 general release

On Tuesday morning Pacific time, Google announced that its Gemini 1.5 Pro model (which we first covered in February) is now available in 180-plus countries, excluding Europe, via the Gemini API in a public preview. This is Google’s most powerful public LLM so far, and it’s available in a free tier that permits up to 50 requests a day.

It supports up to 1 million tokens of input context. As Willison notes in his blog, Gemini 1.5 Pro’s API price at $7/million input tokens and $21/million output tokens costs a little less than GPT-4 Turbo (priced at $10/million in and $30/million out) and more than Claude 3 Sonnet (Anthropic’s mid-tier LLM, priced at $3/million in and $15/million out).

Notably, Gemini 1.5 Pro includes native audio (speech) input processing that allows users to upload audio or video prompts, a new File API for handling files, the ability to add custom system instructions (system prompts) for guiding model responses, and a JSON mode for structured data extraction.

“Majorly Improved” GPT-4 Turbo launch

Enlarge / A GPT-4 Turbo performance chart provided by OpenAI.

Just a bit later than Google’s 1.5 Pro launch on Tuesday, OpenAI announced that it was rolling out a “majorly improved” version of GPT-4 Turbo (a model family originally launched in November) called “gpt-4-turbo-2024-04-09.” It integrates multimodal GPT-4 Vision processing (recognizing the contents of images) directly into the model, and it initially launched through API access only.

Then on Thursday, OpenAI announced that the new GPT-4 Turbo model had just become available for paid ChatGPT users. OpenAI said that the new model improves “capabilities in writing, math, logical reasoning, and coding” and shared a chart that is not particularly useful in judging capabilities (that they later updated). The company also provided an example of an alleged improvement, saying that when writing with ChatGPT, the AI assistant will use “more direct, less verbose, and use more conversational language.”

The vague nature of OpenAI’s GPT-4 Turbo announcements attracted some confusion and criticism online. On X, Willison wrote, “Who will be the first LLM provider to publish genuinely useful release notes?” In some ways, this is a case of “AI vibes” again, as we discussed in our lament about the poor state of LLM benchmarks during the debut of Claude 3. “I’ve not actually spotted any definite differences in quality [related to GPT-4 Turbo],” Willison told us directly in an interview.

The update also expanded GPT-4’s knowledge cutoff to April 2024, although some people are reporting it achieves this through stealth web searches in the background, and others on social media have reported issues with date-related confabulations.

Mistral’s mysterious Mixtral 8x22B release

An illustration of a robot holding a French flag, figuratively reflecting the rise of AI in France due to Mistral. It's hard to draw a picture of an LLM, so a robot will have to do. — Enlarge / An illustration of a robot holding a French flag, figuratively reflecting the rise of AI in France due to Mistral. It’s hard to draw a picture of an LLM, so a robot will have to do.

Not to be outdone, on Tuesday night, French AI company Mistral launched its latest openly licensed model, Mixtral 8x22B, by tweeting a torrent link devoid of any documentation or commentary, much like it has done with previous releases.

The new mixture-of-experts (MoE) release weighs in with a larger parameter count than its previously most-capable open model, Mixtral 8x7B, which we covered in December. It’s rumored to potentially be as capable as GPT-4 (In what way, you ask? Vibes). But that has yet to be seen.

“The evals are still rolling in, but the biggest open question right now is how well Mixtral 8x22B shapes up,” Willison told Ars. “If it’s in the same quality class as GPT-4 and Claude 3 Opus, then we will finally have an openly licensed model that’s not significantly behind the best proprietary ones.”

This release has Willison most excited, saying, “If that thing really is GPT-4 class, it’s wild, because you can run that on a (very expensive) laptop. I think you need 128GB of MacBook RAM for it, twice what I have.”

The new Mixtral is not listed on Chatbot Arena yet, Willison noted, because Mistral has not released a fine-tuned model for chatting yet. It’s still a raw, predict-the-next token LLM. “There’s at least one community instruction tuned version floating around now though,” says Willison.

Chatbot Arena Leaderboard shake-ups

Enlarge / A Chatbot Arena Leaderboard screenshot taken on April 12, 2024.

Benj Edwards

This week’s LLM news isn’t limited to just the big names in the field. There have also been rumblings on social media about the rising performance of open source models like Cohere’s Command R+, which reached position 6 on the LMSYS Chatbot Arena Leaderboard—the highest-ever ranking for an open-weights model.

And for even more Chatbot Arena action, apparently the new version of GPT-4 Turbo is proving competitive with Claude 3 Opus. The two are still in a statistical tie, but GPT-4 Turbo recently pulled ahead numerically. (In March, we reported when Claude 3 first numerically pulled ahead of GPT-4 Turbo, which was then the first time another AI model had surpassed a GPT-4 family model member on the leaderboard.)

Regarding this fierce competition among LLMs—of which most of the muggle world is unaware and will likely never be—Willison told Ars, “The past two months have been a whirlwind—we finally have not just one but several models that are competitive with GPT-4.” We’ll see if OpenAI’s rumored release of GPT-5 later this year will restore the company’s technological lead, we note, which once seemed insurmountable. But for now, Willison says, “OpenAI are no longer the undisputed leaders in LLMs.”

Words are flowing out like endless rain: Recapping a busy week of LLM news Read More »

OpenAI drops login requirements for ChatGPT’s free version

AI, AI assistants, AI models, Anthropic, Antrhopic Claude, Biz & IT, chatgpt, chatgtp, Claude 3, Google, Google Gemini, GPT-3.5, GPT-4, GPT-4-turbo, large language models, machine learning, openai / Shannon Garcia / April 1, 2024

free as in beer? —

ChatGPT 3.5 still falls far short of GPT-4, and other models surpassed it long ago.

Benj Edwards – Apr 1, 2024 10: 31 pm UTC

Benj Edwards

On Monday, OpenAI announced that visitors to the ChatGPT website in some regions can now use the AI assistant without signing in. Previously, the company required that users create an account to use it, even with the free version of ChatGPT that is currently powered by the GPT-3.5 AI language model. But as we have noted in the past, GPT-3.5 is widely known to provide more inaccurate information compared to GPT-4 Turbo, available in paid versions of ChatGPT.

Since its launch in November 2022, ChatGPT has transformed over time from a tech demo to a comprehensive AI assistant, and it’s always had a free version available. The cost is free because “you’re the product,” as the old saying goes. Using ChatGPT helps OpenAI gather data that will help the company train future AI models, although free users and ChatGPT Plus subscription members can both opt out of allowing the data they input into ChatGPT to be used for AI training. (OpenAI says it never trains on inputs from ChatGPT Team and Enterprise members at all).

Opening ChatGPT to everyone could provide a frictionless on-ramp for people who might use it as a substitute for Google Search or potentially gain new customers by providing an easy way for people to use ChatGPT quickly, then offering an upsell to paid versions of the service.

“It’s core to our mission to make tools like ChatGPT broadly available so that people can experience the benefits of AI,” OpenAI says on its blog page. “For anyone that has been curious about AI’s potential but didn’t want to go through the steps to set up an account, start using ChatGPT today.”

When you visit the ChatGPT website, you're immediately presented with a chat box like this (in some regions). Screenshot captured April 1, 2024. — Enlarge / When you visit the ChatGPT website, you’re immediately presented with a chat box like this (in some regions). Screenshot captured April 1, 2024.

Benj Edwards

Since kids will also be able to use ChatGPT without an account—despite it being against the terms of service—OpenAI also says it’s introducing “additional content safeguards,” such as blocking more prompts and “generations in a wider range of categories.” What exactly that entails has not been elaborated upon by OpenAI, but we reached out to the company for comment.

There might be a few other downsides to the fully open approach. On X, AI researcher Simon Willison wrote about the potential for automated abuse as a way to get around paying for OpenAI’s services: “I wonder how their scraping prevention works? I imagine the temptation for people to abuse this as a free 3.5 API will be pretty strong.”

With fierce competition, more GPT-3.5 access may backfire

Willison also mentioned a common criticism of OpenAI (as voiced in this case by Wharton professor Ethan Mollick) that people’s ideas about what AI models can do have so far largely been influenced by GPT-3.5, which, as we mentioned, is far less capable and far more prone to making things up than the paid version of ChatGPT that uses GPT-4 Turbo.

“In every group I speak to, from business executives to scientists, including a group of very accomplished people in Silicon Valley last night, much less than 20% of the crowd has even tried a GPT-4 class model,” wrote Mollick in a tweet from early March.

With models like Google Gemini Pro 1.5 and Anthropic Claude 3 potentially surpassing OpenAI’s best proprietary model at the moment —and open weights AI models eclipsing the free version of ChatGPT—allowing people to use GPT-3.5 might not be putting OpenAI’s best foot forward. Microsoft Copilot, powered by OpenAI models, also supports a frictionless, no-login experience, but it allows access to a model based on GPT-4. But Gemini currently requires a sign-in, and Anthropic sends a login code through email.

For now, OpenAI says the login-free version of ChatGPT is not yet available to everyone, but it will be coming soon: “We’re rolling this out gradually, with the aim to make AI accessible to anyone curious about its capabilities.”

OpenAI drops login requirements for ChatGPT’s free version Read More »

Apple may hire Google to power new iPhone AI features using Gemini—report

AI, Apple, Biz & IT, chatgpt, chatgtp, cloud AI, Gemini, Google, Google Gemini, GPT-4, image synthesis, iOS, large language models, llm, machine learning, openai, Siri, text synthesis / Kelly Newman / March 18, 2024

Bake a cake as fast as you can —

With Apple’s own AI tech lagging behind, the firm looks for a fallback solution.

Benj Edwards – Mar 18, 2024 7: 56 pm UTC

On Monday, Bloomberg reported that Apple is in talks to license Google’s Gemini model to power AI features like Siri in a future iPhone software update coming later in 2024, according to people familiar with the situation. Apple has also reportedly conducted similar talks with ChatGPT maker OpenAI.

The potential integration of Google Gemini into iOS 18 could bring a range of new cloud-based (off-device) AI-powered features to Apple’s smartphone, including image creation or essay writing based on simple prompts. However, the terms and branding of the agreement have not yet been finalized, and the implementation details remain unclear. The companies are unlikely to announce any deal until Apple’s annual Worldwide Developers Conference in June.

Gemini could also bring new capabilities to Apple’s widely criticized voice assistant, Siri, which trails newer AI assistants powered by large language models (LLMs) in understanding and responding to complex questions. Rumors of Apple’s own internal frustration with Siri—and potential remedies—have been kicking around for some time. In January, 9to5Mac revealed that Apple had been conducting tests with a beta version of iOS 17.4 that used OpenAI’s ChatGPT API to power Siri.

As we have previously reported, Apple has also been developing its own AI models, including a large language model codenamed Ajax and a basic chatbot called Apple GPT. However, the company’s LLM technology is said to lag behind that of its competitors, making a partnership with Google or another AI provider a more attractive option.

Google launched Gemini, a language-based AI assistant similar to ChatGPT, in December and has updated it several times since. Many industry experts consider the larger Gemini models to be roughly as capable as OpenAI’s GPT-4 Turbo, which powers the subscription versions of ChatGPT. Until just recently, with the emergence of Gemini Ultra and Claude 3, OpenAI’s top model held a fairly wide lead in perceived LLM capability.

The potential partnership between Apple and Google could significantly impact the AI industry, as Apple’s platform represents more than 2 billion active devices worldwide. If the agreement gets finalized, it would build upon the existing search partnership between the two companies, which has seen Google pay Apple billions of dollars annually to make its search engine the default option on iPhones and other Apple devices.

However, Bloomberg reports that the potential partnership between Apple and Google is likely to draw scrutiny from regulators, as the companies’ current search deal is already the subject of a lawsuit by the US Department of Justice. The European Union is also pressuring Apple to make it easier for consumers to change their default search engine away from Google.

With so much potential money on the line, selecting Google for Apple’s cloud AI job could potentially be a major loss for OpenAI in terms of bringing its technology widely into the mainstream—with a market representing billions of users. Even so, any deal with Google or OpenAI may be a temporary fix until Apple can get its own LLM-based AI technology up to speed.

Apple may hire Google to power new iPhone AI features using Gemini—report Read More »

OpenAI CEO Altman wasn’t fired because of scary new tech, just internal politics

AI, AI ethics, AI safety, Biz & IT, chatgpt, chatgtp, GPT-4, greg brockman, Helen Toner, large language models, machine learning, openai, sam altman, WilmerHale / Kelly Newman / March 11, 2024

Adventures in optics —

As Altman cements power, OpenAI announces three new board members—and a returning one.

Benj Edwards – Mar 11, 2024 3: 04 pm UTC

Enlarge / OpenAI CEO Sam Altman speaks during the OpenAI DevDay event on November 6, 2023, in San Francisco.

On Friday afternoon Pacific Time, OpenAI announced the appointment of three new members to the company’s board of directors and released the results of an independent review of the events surrounding CEO Sam Altman’s surprise firing last November. The current board expressed its confidence in the leadership of Altman and President Greg Brockman, and Altman is rejoining the board.

The newly appointed board members are Dr. Sue Desmond-Hellmann, former CEO of the Bill and Melinda Gates Foundation; Nicole Seligman, former EVP and global general counsel of Sony; and Fidji Simo, CEO and chair of Instacart. These additions notably bring three women to the board after OpenAI met criticism about its restructured board composition last year. In addition, Sam Altman has rejoined the board.

The independent review, conducted by law firm WilmerHale, investigated the circumstances that led to Altman’s abrupt removal from the board and his termination as CEO on November 17, 2023. Despite rumors to the contrary, the board did not fire Altman because they got a peek at scary new AI technology and flinched. “WilmerHale… found that the prior Board’s decision did not arise out of concerns regarding product safety or security, the pace of development, OpenAI’s finances, or its statements to investors, customers, or business partners.”

Instead, the review determined that the prior board’s actions stemmed from a breakdown in trust between the board and Altman.

After reportedly interviewing dozens of people and reviewing over 30,000 documents, WilmerHale found that while the prior board acted within its purview, Altman’s termination was unwarranted. “WilmerHale found that the prior Board acted within its broad discretion to terminate Mr. Altman,” OpenAI wrote, “but also found that his conduct did not mandate removal.”

Additionally, the law firm found that the decision to fire Altman was made in undue haste: “The prior Board implemented its decision on an abridged timeframe, without advance notice to key stakeholders and without a full inquiry or an opportunity for Mr. Altman to address the prior Board’s concerns.”

Altman’s surprise firing occurred after he attempted to remove Helen Toner from OpenAI’s board due to disagreements over her criticism of OpenAI’s approach to AI safety and hype. Some board members saw his actions as deceptive and manipulative. After Altman returned to OpenAI, Toner resigned from the OpenAI board on November 29.

In a statement posted on X, Altman wrote, “i learned a lot from this experience. one think [sic] i’ll say now: when i believed a former board member was harming openai through some of their actions, i should have handled that situation with more grace and care. i apologize for this, and i wish i had done it differently.”

Enlarge / A tweet from Sam Altman posted on March 8, 2024.

Following the review’s findings, the Special Committee of the OpenAI Board recommended endorsing the November 21 decision to rehire Altman and Brockman. The board also announced several enhancements to its governance structure, including new corporate governance guidelines, a strengthened Conflict of Interest Policy, a whistleblower hotline, and additional board committees focused on advancing OpenAI’s mission.

After OpenAI’s announcements on Friday, resigned OpenAI board members Toner and Tasha McCauley released a joint statement on X. “Accountability is important in any company, but it is paramount when building a technology as potentially world-changing as AGI,” they wrote. “We hope the new board does its job in governing OpenAI and holding it accountable to the mission. As we told the investigators, deception, manipulation, and resistance to thorough oversight should be unacceptable.”

OpenAI CEO Altman wasn’t fired because of scary new tech, just internal politics Read More »

Microsoft partners with OpenAI-rival Mistral for AI models, drawing EU scrutiny

AI, AI Act, Biz & IT, chatgpt, chatgtp, EU AI Act, EU regulation, france, French AI models, French models, GPT-4, GPT-4-turbo, large language models, machine learning, Mistral, Mistral Large, openai / Shannon Garcia / February 29, 2024

The European Approach —

15M euro investment comes as Microsoft hosts Mistral’s GPT-4 alternatives on Azure.

Benj Edwards – Feb 28, 2024 8: 48 pm UTC

Velib bicycles are parked in front of the the U.S. computer and micro-computing company headquarters Microsoft on January 25, 2023 in Issy-les-Moulineaux, France.

On Monday, Microsoft announced plans to offer AI models from Mistral through its Azure cloud computing platform, which came in conjunction with a 15 million euro non-equity investment in the French firm, which is often seen as a European rival to OpenAI. Since then, the investment deal has faced scrutiny from European Union regulators.

Microsoft’s deal with Mistral, known for its large language models akin to OpenAI’s GPT-4 (which powers the subscription versions of ChatGPT), marks a notable expansion of its AI portfolio at a time when its well-known investment in California-based OpenAI has raised regulatory eyebrows. The new deal with Mistral drew particular attention from regulators because Microsoft’s investment could convert into equity (partial ownership of Mistral as a company) during Mistral’s next funding round.

The development has intensified ongoing investigations into Microsoft’s practices, particularly related to the tech giant’s dominance in the cloud computing sector. According to Reuters, EU lawmakers have voiced concerns that Mistral’s recent lobbying for looser AI regulations might have been influenced by its relationship with Microsoft. These apprehensions are compounded by the French government’s denial of prior knowledge of the deal, despite earlier lobbying for more lenient AI laws in Europe. The situation underscores the complex interplay between national interests, corporate influence, and regulatory oversight in the rapidly evolving AI landscape.

Avoiding American influence

The EU’s reaction to the Microsoft-Mistral deal reflects broader tensions over the role of Big Tech companies in shaping the future of AI and their potential to stifle competition. Calls for a thorough investigation into Microsoft and Mistral’s partnership have been echoed across the continent, according to Reuters, with some lawmakers accusing the firms of attempting to undermine European legislative efforts aimed at ensuring a fair and competitive digital market.

The controversy also touches on the broader debate about “European champions” in the tech industry. France, along with Germany and Italy, had advocated for regulatory exemptions to protect European startups. However, the Microsoft-Mistral deal has led some, like MEP Kim van Sparrentak, to question the motives behind these exemptions, suggesting they might have inadvertently favored American Big Tech interests.

“That story seems to have been a front for American-influenced Big Tech lobby,” said Sparrentak, as quoted by Reuters. Sparrentak has been a key architect of the EU’s AI Act, which has not yet been passed. “The Act almost collapsed under the guise of no rules for ‘European champions,’ and now look. European regulators have been played.”

MEP Alexandra Geese also expressed concerns over the concentration of money and power resulting from such partnerships, calling for an investigation. Max von Thun, Europe director at the Open Markets Institute, emphasized the urgency of investigating the partnership, criticizing Mistral’s reported attempts to influence the AI Act.

Also on Monday, amid the partnership news, Mistral announced Mistral Large, a new large language model (LLM) that Mistral says “ranks directly after GPT-4 based on standard benchmarks.” Mistral has previously released several open-weights AI models that have made news for their capabilities, but Mistral Large will be a closed model only available to customers through an API.

Microsoft partners with OpenAI-rival Mistral for AI models, drawing EU scrutiny Read More »

OpenAI accuses NYT of hacking ChatGPT to set up copyright suit

AI, chatbot, chatgpt, copyright infringement, copyright law, DMCA, generative ai, GPT-2, GPT-3.5, GPT-4, new york times, openai, Policy, Web Scraping / DJ Henderson / February 28, 2024

OpenAI is now boldly claiming that The New York Times “paid someone to hack OpenAI’s products” like ChatGPT to “set up” a lawsuit against the leading AI maker.

In a court filing Monday, OpenAI alleged that “100 examples in which some version of OpenAI’s GPT-4 model supposedly generated several paragraphs of Times content as outputs in response to user prompts” do not reflect how normal people use ChatGPT.

Instead, it allegedly took The Times “tens of thousands of attempts to generate” these supposedly “highly anomalous results” by “targeting and exploiting a bug” that OpenAI claims it is now “committed to addressing.”

According to OpenAI this activity amounts to “contrived attacks” by a “hired gun”—who allegedly hacked OpenAI models until they hallucinated fake NYT content or regurgitated training data to replicate NYT articles. NYT allegedly paid for these “attacks” to gather evidence to support The Times’ claims that OpenAI’s products imperil its journalism by allegedly regurgitating reporting and stealing The Times’ audiences.

“Contrary to the allegations in the complaint, however, ChatGPT is not in any way a substitute for a subscription to The New York Times,” OpenAI argued in a motion that seeks to dismiss the majority of The Times’ claims. “In the real world, people do not use ChatGPT or any other OpenAI product for that purpose. Nor could they. In the ordinary course, one cannot use ChatGPT to serve up Times articles at will.”

In the filing, OpenAI described The Times as enthusiastically reporting on its chatbot developments for years without raising any concerns about copyright infringement. OpenAI claimed that it disclosed that The Times’ articles were used to train its AI models in 2020, but The Times only cared after ChatGPT’s popularity exploded after its debut in 2022.

According to OpenAI, “It was only after this rapid adoption, along with reports of the value unlocked by these new technologies, that the Times claimed that OpenAI had ‘infringed its copyright[s]’ and reached out to demand ‘commercial terms.’ After months of discussions, the Times filed suit two days after Christmas, demanding ‘billions of dollars.'”

Ian Crosby, Susman Godfrey partner and lead counsel for The New York Times, told Ars that “what OpenAI bizarrely mischaracterizes as ‘hacking’ is simply using OpenAI’s products to look for evidence that they stole and reproduced The Times’s copyrighted works. And that is exactly what we found. In fact, the scale of OpenAI’s copying is much larger than the 100-plus examples set forth in the complaint.”

Crosby told Ars that OpenAI’s filing notably “doesn’t dispute—nor can they—that they copied millions of The Times’ works to build and power its commercial products without our permission.”

“Building new products is no excuse for violating copyright law, and that’s exactly what OpenAI has done on an unprecedented scale,” Crosby said.

OpenAI argued that the court should dismiss claims alleging direct copyright, contributory infringement, Digital Millennium Copyright Act violations, and misappropriation, all of which it describes as “legally infirm.” Some fail because they are time-barred—seeking damages on training data for OpenAI’s older models—OpenAI claimed. Others allegedly fail because they misunderstand fair use or are preempted by federal laws.

If OpenAI’s motion is granted, the case would be substantially narrowed.

But if the motion is not granted and The Times ultimately wins—and it might—OpenAI may be forced to wipe ChatGPT and start over.

“OpenAI, which has been secretive and has deliberately concealed how its products operate, is now asserting it’s too late to bring a claim for infringement or hold them accountable. We disagree,” Crosby told Ars. “It’s noteworthy that OpenAI doesn’t dispute that it copied Times works without permission within the statute of limitations to train its more recent and current models.”

OpenAI did not immediately respond to Ars’ request to comment.

OpenAI accuses NYT of hacking ChatGPT to set up copyright suit Read More »

OpenAI experiments with giving ChatGPT a long-term conversation memory

AI, AI memory, Biz & IT, chatbot, chatbots, chatgpt, chatgtp, GPT-4, GPT-4-turbo, large language models, machine learning / Shannon Garcia / February 14, 2024

“I remember…the Alamo” —

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

Benj Edwards – Feb 13, 2024 10: 01 pm UTC

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).

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.”

OpenAI experiments with giving ChatGPT a long-term conversation memory Read More »

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

agentic AI, AI, AI agents, Biz & IT, chatgpt, ChatGPT Plus, chatgtp, GPT Store, GPT-4, GPT-4-turbo, GPTs, large language models, machine learning, openai / DJ Henderson / January 31, 2024

team of rivals —

Bring different AI roles into the same chatbot conversation history.

Benj Edwards – Jan 31, 2024 10: 34 pm UTC

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.

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 »

OpenAI updates ChatGPT-4 model with potential fix for AI “laziness” problem

AI, AI assitants, AI laziness, Biz & IT, chatgpt, ChatGPT-4, chatgtp, GPT-3, GPT-3.5, gpt-3.5-turbo, GPT-4, GPT-4-turbo, large language models, openai / DJ Henderson / January 26, 2024

Break’s over —

Also, new GPT-3.5 Turbo model, lower API prices, and other model updates.

Benj Edwards – Jan 26, 2024 5: 26 pm UTC

A lazy robot (a man with a box on his head) sits on the floor beside a couch.

On Thursday, OpenAI announced updates to the AI models that power its ChatGPT assistant. Amid less noteworthy updates, OpenAI tucked in a mention of a potential fix to a widely reported “laziness” problem seen in GPT-4 Turbo since its release in November. The company also announced a new GPT-3.5 Turbo model (with lower pricing), a new embedding model, an updated moderation model, and a new way to manage API usage.

“Today, we are releasing an updated GPT-4 Turbo preview model, gpt-4-0125-preview. This model completes tasks like code generation more thoroughly than the previous preview model and is intended to reduce cases of ‘laziness’ where the model doesn’t complete a task,” writes OpenAI in its blog post.

Since the launch of GPT-4 Turbo, a large number of ChatGPT users have reported that the ChatGPT-4 version of its AI assistant has been declining to do tasks (especially coding tasks) with the same exhaustive depth as it did in earlier versions of GPT-4. We’ve seen this behavior ourselves while experimenting with ChatGPT over time.

OpenAI has never offered an official explanation for this change in behavior, but OpenAI employees have previously acknowledged on social media that the problem is real, and the ChatGPT X account wrote in December, “We’ve heard all your feedback about GPT4 getting lazier! we haven’t updated the model since Nov 11th, and this certainly isn’t intentional. model behavior can be unpredictable, and we’re looking into fixing it.”

We reached out to OpenAI asking if it could provide an official explanation for the laziness issue but did not receive a response by press time.

New GPT-3.5 Turbo, other updates

Elsewhere in OpenAI’s blog update, the company announced a new version of GPT-3.5 Turbo (gpt-3.5-turbo-0125), which it says will offer “various improvements including higher accuracy at responding in requested formats and a fix for a bug which caused a text encoding issue for non-English language function calls.”

And the cost of GPT-3.5 Turbo through OpenAI’s API will decrease for the third time this year “to help our customers scale.” New input token prices are 50 percent less, at $0.0005 per 1,000 input tokens, and output prices are 25 percent less, at $0.0015 per 1,000 output tokens.

Lower token prices for GPT-3.5 Turbo will make operating third-party bots significantly less expensive, but the GPT-3.5 model is generally more likely to confabulate than GPT-4 Turbo. So we might see more scenarios like Quora’s bot telling people that eggs can melt (although the instance used a now-deprecated GPT-3 model called text-davinci-003). If GPT-4 Turbo API prices drop over time, some of those hallucination issues with third parties might eventually go away.

OpenAI also announced new embedding models, text-embedding-3-small and text-embedding-3-large, which convert content into numerical sequences, aiding in machine learning tasks like clustering and retrieval. And an updated moderation model, text-moderation-007, is part of the company’s API that “allows developers to identify potentially harmful text,” according to OpenAI.

Finally, OpenAI is rolling out improvements to its developer platform, introducing new tools for managing API keys and a new dashboard for tracking API usage. Developers can now assign permissions to API keys from the API keys page, helping to clamp down on misuse of API keys (if they get into the wrong hands) that can potentially cost developers lots of money. The API dashboard allows devs to “view usage on a per feature, team, product, or project level, simply by having separate API keys for each.”

As the media world seemingly swirls around the company with controversies and think pieces about the implications of its tech, releases like these show that the dev teams at OpenAI are still rolling along as usual with updates at a fairly regular pace. Despite the company almost completely falling apart late last year, it seems that, under the hood, it’s business as usual for OpenAI.

OpenAI updates ChatGPT-4 model with potential fix for AI “laziness” problem Read More »

Everybody’s talking about Mistral, an upstart French challenger to OpenAI

AI, Anthropic, Arthur Mensch, Biz & IT, chatgpt, chatgtp, france, GPT-3, GPT-3.5, GPT-4, large language models, LLaMA, Llama 2, machine learning, Meta, Mistral, Mistral AI, Mixtral, Mixtral 8x7B, openai, Paris / Shannon Garcia / December 12, 2023

A challenger appears —

“Mixture of experts” Mixtral 8x7B helps open-weights AI punch above its weight class.

Benj Edwards – Dec 12, 2023 8: 15 pm UTC

An illustrated robot holding a French flag. — Enlarge / An illustration of a robot holding a French flag, figuratively reflecting the rise of AI in France due to Mistral. It’s hard to draw a picture of an LLM, so a robot will have to do.

On Monday, Mistral AI announced a new AI language model called Mixtral 8x7B, a “mixture of experts” (MoE) model with open weights that reportedly truly matches OpenAI’s GPT-3.5 in performance—an achievement that has been claimed by others in the past but is being taken seriously by AI heavyweights such as OpenAI’s Andrej Karpathy and Jim Fan. That means we’re closer to having a ChatGPT-3.5-level AI assistant that can run freely and locally on our devices, given the right implementation.

Mistral, based in Paris and founded by Arthur Mensch, Guillaume Lample, and Timothée Lacroix, has seen a rapid rise in the AI space recently. It has been quickly raising venture capital to become a sort of French anti-OpenAI, championing smaller models with eye-catching performance. Most notably, Mistral’s models run locally with open weights that can be downloaded and used with fewer restrictions than closed AI models from OpenAI, Anthropic, or Google. (In this context “weights” are the computer files that represent a trained neural network.)

Mixtral 8x7B can process a 32K token context window and works in French, German, Spanish, Italian, and English. It works much like ChatGPT in that it can assist with compositional tasks, analyze data, troubleshoot software, and write programs. Mistral claims that it outperforms Meta’s much larger LLaMA 2 70B (70 billion parameter) large language model and that it matches or exceeds OpenAI’s GPT-3.5 on certain benchmarks, as seen in the chart below.

Enlarge / A chart of Mixtral 8x7B performance vs. LLaMA 2 70B and GPT-3.5, provided by Mistral.

Mistral

The speed at which open-weights AI models have caught up with OpenAI’s top offering a year ago has taken many by surprise. Pietro Schirano, the founder of EverArt, wrote on X, “Just incredible. I am running Mistral 8x7B instruct at 27 tokens per second, completely locally thanks to @LMStudioAI. A model that scores better than GPT-3.5, locally. Imagine where we will be 1 year from now.”

LexicaArt founder Sharif Shameem tweeted, “The Mixtral MoE model genuinely feels like an inflection point — a true GPT-3.5 level model that can run at 30 tokens/sec on an M1. Imagine all the products now possible when inference is 100% free and your data stays on your device.” To which Andrej Karpathy replied, “Agree. It feels like the capability / reasoning power has made major strides, lagging behind is more the UI/UX of the whole thing, maybe some tool use finetuning, maybe some RAG databases, etc.”

Mixture of experts

So what does mixture of experts mean? As this excellent Hugging Face guide explains, it refers to a machine-learning model architecture where a gate network routes input data to different specialized neural network components, known as “experts,” for processing. The advantage of this is that it enables more efficient and scalable model training and inference, as only a subset of experts are activated for each input, reducing the computational load compared to monolithic models with equivalent parameter counts.

In layperson’s terms, a MoE is like having a team of specialized workers (the “experts”) in a factory, where a smart system (the “gate network”) decides which worker is best suited to handle each specific task. This setup makes the whole process more efficient and faster, as each task is done by an expert in that area, and not every worker needs to be involved in every task, unlike in a traditional factory where every worker might have to do a bit of everything.

OpenAI has been rumored to use a MoE system with GPT-4, accounting for some of its performance. In the case of Mixtral 8x7B, the name implies that the model is a mixture of eight 7 billion-parameter neural networks, but as Karpathy pointed out in a tweet, the name is slightly misleading because, “it is not all 7B params that are being 8x’d, only the FeedForward blocks in the Transformer are 8x’d, everything else stays the same. Hence also why total number of params is not 56B but only 46.7B.”

Mixtral is not the first “open” mixture of experts model, but it is notable for its relatively small size in parameter count and performance. It’s out now, available on Hugging Face and BitTorrent under the Apache 2.0 license. People have been running it locally using an app called LM Studio. Also, Mistral began offering beta access to an API for three levels of Mistral models on Monday.

Everybody’s talking about Mistral, an upstart French challenger to OpenAI Read More »

As ChatGPT gets “lazy,” people test “winter break hypothesis” as the cause

AI, Biz & IT, chatgpt, ChatGPT lazy, chatgtp, GPT-3.5, GPT-4, machine learning, openai, winter break hypothesis / DJ Henderson / December 11, 2023

only 14 shopping days ’til Christmas —

Unproven hypothesis seeks to explain ChatGPT’s seemingly new reluctance to do hard work.

Benj Edwards – Dec 11, 2023 10: 50 pm UTC

A hand moving a wooden calendar piece that says

In late November, some ChatGPT users began to notice that ChatGPT-4 was becoming more “lazy,” reportedly refusing to do some tasks or returning simplified results. Since then, OpenAI has admitted that it’s an issue, but the company isn’t sure why. The answer may be what some are calling “winter break hypothesis.” While unproven, the fact that AI researchers are taking it seriously shows how weird the world of AI language models has become.

“We’ve heard all your feedback about GPT4 getting lazier!” tweeted the official ChatGPT account on Thursday. “We haven’t updated the model since Nov 11th, and this certainly isn’t intentional. model behavior can be unpredictable, and we’re looking into fixing it.”

On Friday, an X account named Martian openly wondered if LLMs might simulate seasonal depression. Later, Mike Swoopskee tweeted, “What if it learned from its training data that people usually slow down in December and put bigger projects off until the new year, and that’s why it’s been more lazy lately?”

Since the system prompt for ChatGPT feeds the bot the current date, people noted, some began to think there may be something to the idea. Why entertain such a weird supposition? Because research has shown that large language models like GPT-4, which powers the paid version of ChatGPT, respond to human-style encouragement, such as telling a bot to “take a deep breath” before doing a math problem. People have also less formally experimented with telling an LLM that it will receive a tip for doing the work, or if an AI model gets lazy, telling the bot that you have no fingers seems to help lengthen outputs.

“Winter break hypothesis” test result screenshots from Rob Lynch on X.
“Winter break hypothesis” test result screenshots from Rob Lynch on X.
“Winter break hypothesis” test result screenshots from Rob Lynch on X.

On Monday, a developer named Rob Lynch announced on X that he had tested GPT-4 Turbo through the API over the weekend and found shorter completions when the model is fed a December date (4,086 characters) than when fed a May date (4,298 characters). Lynch claimed the results were statistically significant. However, a reply from AI researcher Ian Arawjo said that he could not reproduce the results with statistical significance. (It’s worth noting that reproducing results with LLM can be difficult because of random elements at play that vary outputs over time, so people sample a large number of responses.)

As of this writing, others are busy running tests, and the results are inconclusive. This episode is a window into the quickly unfolding world of LLMs and a peek into an exploration into largely unknown computer science territory. As AI researcher Geoffrey Litt commented in a tweet, “funniest theory ever, I hope this is the actual explanation. Whether or not it’s real, [I] love that it’s hard to rule out.”

A history of laziness

One of the reports that started the recent trend of noting that ChatGPT is getting “lazy” came on November 24 via Reddit, the day after Thanksgiving in the US. There, a user wrote that they asked ChatGPT to fill out a CSV file with multiple entries, but ChatGPT refused, saying, “Due to the extensive nature of the data, the full extraction of all products would be quite lengthy. However, I can provide the file with this single entry as a template, and you can fill in the rest of the data as needed.”

On December 1, OpenAI employee Will Depue confirmed in an X post that OpenAI was aware of reports about laziness and was working on a potential fix. “Not saying we don’t have problems with over-refusals (we definitely do) or other weird things (working on fixing a recent laziness issue), but that’s a product of the iterative process of serving and trying to support sooo many use cases at once,” he wrote.

It’s also possible that ChatGPT was always “lazy” with some responses (since the responses vary randomly), and the recent trend made everyone take note of the instances in which they are happening. For example, in June, someone complained of GPT-4 being lazy on Reddit. (Maybe ChatGPT was on summer vacation?)

Also, people have been complaining about GPT-4 losing capability since it was released. Those claims have been controversial and difficult to verify, making them highly subjective.

As Ethan Mollick joked on X, as people discover new tricks to improve LLM outputs, prompting for large language models is getting weirder and weirder: “It is May. You are very capable. I have no hands, so do everything. Many people will die if this is not done well. You really can do this and are awesome. Take a deep breathe and think this through. My career depends on it. Think step by step.”

As ChatGPT gets “lazy,” people test “winter break hypothesis” as the cause Read More »