Customers were supposed to be able to drive up, loudly state their orders into the drive-thru microphone, and then have an AI record all of that, instead of a human crew member. Theoretically, the AI should be able to comprehend more complicated requests, offer recommendations based on past orders and also reduce error, all while simultaneously continuing to provide fast service and without getting bogged down by staffing problems.

Yet McDonald’s is already giving up on the AI drive-thru feature just a few years after introducing it. Viral videos exposed the system as overwhelmed with more simple orders, taking requests from the wrong cars and recommending peculiar food couplings, like ice cream and bacon. Following these public failures, McDonald’s declared that it will no longer use IBM for the partnership after July 31, 2024.

This spectacular flameout raises the question: does AI really have a role to play in the drive-thru of the future, or is ‘Burgerbot’ just destined to be the next in a long line of extremely smart things that fundamentally, scornfully refuse to understand humans and, thus, fail?

The pros of AI drive-thrus 

But McDonald’s woes aside, the benefits that attracted the company and competitors to AI drive-thrus in the first place haven’t disappeared. Labour costs are going up while staff are getting harder to find, so the prospect of having an AI take orders could offer significant cost reductions in the future.

AI systems also promise something extremely compelling: absolute understanding of even the most twisted, crazy customer issues or requests you can think of. Armed with prior ordering data, the AI was able to provide custom recommendations aimed at boosting average spend.

AI ordering, furthermore, could lead to an even speedier, less-friction-filled drive-thru experience. An AI could immediately process an order rather than requiring a human crew member to repeat it back. Those efficiencies could be even more significant during peak hours when cars are sprawled around the building and the drive-thru is jammed.

The negatives – and where McDonald has stumbled

Of course, the viral blunders that shut down McDonald’s AI drive-thru dreams tells a cautionary tale true to life when it comes to some of the real pitfalls with which this new tech grapples. Despite years of training, McDonald’s AI system still seemed to frequently fail at the very core task of taking accurate orders.

And such failures during the ordering process could result in customer dissatisfaction and expensive order inaccuracies – which in turn could wipe out any potential labour savings. And then there is the looming question of whether AI will ever be able to understand the constant stream of idiosyncratic phrasings, accents, and off-menu requests as well as humans.

The McDonald’s experience also hints at the “uncanny valley” challenge of AI-powered ordering. While often impressive, the current state of AI can still produce responses that seem almost human, but not quite – leading to an unsettling experience for some customers. A human voice actor may be required to dub over the AI.

The future of AI drive-thrus 

Despite pulling the plug on its initial system, the fast food giant still believes AI will be a big player in the drive-thrus of the future. The IBM project, which testing gave the company “confidence that a voice ordering solution for drive-thru will be part of our restaurants’ future,” is part of a broader effort by McDonald’s to develop “long-term, scalable solutions,” a company spokesperson said.

Chipotle, Wendy’s, Taco Bell, and Pizza Hut are among a number of other big chains that are also making big moves to integrate AI drive-thru ordering into their businesses. The stakes are high, with the entire industry standing to save billions in labour costs if this technology works.

The consensus among most experts, however, is that AI drive-thru ordering is just beginning and that major milestones must still be met before it goes truly universal. But with AI language models advancing so fast, it may not be long before the ordering-caution and other ordering issue plaguing McDonald’s will be a thing of the past.

There may also be a phased handoff period where passengers have the choice of interacting with an AI or a human flight attendant. It might build rapport and increase trust over time, which might be an advantage for AI drive-thrus.

But at the end of the day, it sounds like McDonalds was still a few months to years ahead of the curve and just rolled this out more aggressively than it should have right away. Or, as one Silicon Valley investor quipped yesterday: “You can’t be a pioneer without taking a few arrows in the back.” For the fast-food industry, streamlining drive-thrus with AI remains the next frontier – it’s just going to take more time.

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According to a Bloomberg report by Mark Gurman, “Apple isn’t paying OpenAI as part of the partnership.”

Instead, the Cupertino-based company is leveraging its massive user base and device ecosystem as currency.

“Apple believes pushing OpenAI’s brand and technology to hundreds of millions of its devices is of equal or greater value than monetary payments,” Gurman’s sources explained.

Gurman notes that OpenAI could find a silver lining by encouraging Apple users to subscribe to ChatGPT Plus, priced at $20 per month. If subscribers sign up through Apple devices, the iPhone maker will likely even claim a commission.

Apple’s AI strategy extends beyond OpenAI. The company is reportedly in talks to offer Google’s Gemini chatbot as an additional option later this year, signalling its intent to provide users with diverse AI experiences without necessarily having to make such major investments itself.

The long-term vision for Apple involves capturing a slice of the revenue generated from monetising chatbot results on its operating systems. This move anticipates a shift in user behaviour, with more people relying on AI assistants rather than traditional search engines like Google.

While Apple’s AI plans are ambitious, challenges remain. The report highlights that the company has yet to secure a deal with a local Chinese provider for chatbot features, though discussions with local firms like Baidu and Alibaba are underway. Initially, Apple Intelligence will be limited to US English, with expanded language support planned for the following year.

The Apple-OpenAI deal represents a novel approach to collaboration in the AI space, where brand exposure and technological integration are valued as much as, if not more than, direct financial compensation.

See also: Musk ends OpenAI lawsuit while slamming Apple’s ChatGPT plans

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Musk had initially sued OpenAI in March 2024, alleging breach of contracts, unfair business practices, and failure in fiduciary duty. He claimed that his contributions to the company were made “in exchange for and in reliance on promises that those assets were irrevocably dedicated to building AI for public benefit, with only safety as a countervailing concern.”

The lawsuit sought remedies for “breach of contract, promissory estoppel, breach of fiduciary duty, unfair business practices, and accounting,” as well as specific performance, restitution, and damages.

However, Musk’s filings to withdraw the case provided no explanation for abandoning the lawsuit. OpenAI had previously called Musk’s claims “incoherent” and that his inability to produce a contract made his breach claims difficult to prove, stating that documents provided by Musk “contradict his allegations as to the alleged terms of the agreement.”

The withdrawal of the lawsuit comes at a time when Musk is strongly opposing Apple’s plans to integrate ChatGPT into its operating systems.

During Apple’s keynote event announcing Apple Intelligence for iOS 18, iPadOS 18, and macOS Sequoia, Musk threatened to ban Apple devices from his companies, calling the integration “an unacceptable security violation.”

Despite assurances from Apple and OpenAI that user data would only be shared with explicit consent and that interactions would be secure, Musk questioned Apple’s ability to ensure data security, stating, “Apple has no clue what’s actually going on once they hand your data over to OpenAI. They’re selling you down the river.”

Since bringing the lawsuit against OpenAI, Musk has also created his own AI company, xAI, and secured over $6 billion in funding for his plans to advance the Grok chatbot on his social network, X.

While Musk’s reasoning for dropping the OpenAI lawsuit remains unclear, his actions suggest a potential shift in focus towards advancing his own AI endeavours while continuing to vocalise his criticism of OpenAI through social media rather than the courts.

See also: DuckDuckGo releases portal giving private access to AI models

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The service, accessible at Duck.ai, is globally available and features a light and clean user interface. Users can choose from four AI models: two closed-source models and two open-source models. The closed-source models are OpenAI’s GPT-3.5 Turbo and Anthropic’s Claude 3 Haiku, while the open-source models are Meta’s Llama-3 70B and Mistral AI’s Mixtral 8x7b.

What sets DuckDuckGo AI Chat apart is its commitment to user privacy. Neither DuckDuckGo nor the chatbot providers can use user data to train their models, ensuring that interactions remain private and anonymous. DuckDuckGo also strips away metadata, such as server or IP addresses, so that queries appear to originate from the company itself rather than individual users.

The company has agreements in place with all model providers to ensure that any saved chats are completely deleted within 30 days, and that none of the chats made on the platform can be used to train or improve the models. This makes preserving privacy easier than changing the privacy settings for each service.

In an era where online services are increasingly hungry for user data, DuckDuckGo’s AI Chat service is a breath of fresh air. The company’s commitment to privacy is a direct response to the growing concerns about data collection and usage in the AI industry. By providing a private and anonymous platform for users to interact with AI chatbots, DuckDuckGo is setting a new standard for the industry.

DuckDuckGo’s AI service is free to use within a daily limit, and the company is considering launching a paid tier to reduce or eliminate these limits. The service is designed to be a complementary partner to its search engine, allowing users to switch between search and AI chat for a more comprehensive search experience.

“We view AI Chat and search as two different but powerful tools to help you find what you’re looking for – especially when you’re exploring a new topic. You might be shopping or doing research for a project and are unsure how to get started. In situations like these, either AI Chat or Search could be good starting points.” the company explained.

“If you start by asking a few questions in AI Chat, the answers may inspire traditional searches to track down reviews, prices, or other primary sources. If you start with Search, you may want to switch to AI Chat for follow-up queries to help make sense of what you’ve read, or for quick, direct answers to new questions that weren’t covered in the web pages you saw.”

To accommodate that user workflow, DuckDuckGo has made AI Chat accessible through DuckDuckGo Private Search for quick access.

The launch of DuckDuckGo AI Chat comes at a time when the AI industry is facing increasing scrutiny over data privacy and usage. The service is a welcome addition for privacy-conscious individuals, joining the recent launch of Venice AI by crypto entrepreneur Erik Voorhees. Venice AI features an uncensored AI chatbot and image generator that doesn’t require accounts and doesn’t retain data..

As the AI industry continues to evolve, it’s clear that privacy will remain a top concern for users. With the launch of DuckDuckGo AI Chat, the company is taking a significant step towards providing users with a private and secure platform for interacting with AI chatbots.

See also: AI pioneers turn whistleblowers and demand safeguards

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Recently, Arm unveiled new chip blueprints and software tools aimed at enhancing smartphones’ ability to handle AI tasks more efficiently. But they didn’t stop there – Arm also implemented changes to how they deliver these blueprints, potentially accelerating adoption.

Arm is evolving its solution offerings to maximise the benefits of leading process nodes. They announced the Arm Compute Subsystems (CSS) for Client, their latest cutting-edge compute solution tailored for AI applications in smartphones and PCs.

This CSS for Client promises a significant performance leap – we’re talking over 30% increased compute and graphics performance, along with an impressive 59% faster AI inference for AI, machine learning, and computer vision workloads.

While Arm’s technology powered the smartphone revolution, it’s also gaining traction in PCs and data centres, where energy efficiency is prized. Though smartphones remain Arm’s biggest market, supplying IP to rivals like Apple, Qualcomm, and MediaTek, the company is expanding its offerings.

They’ve launched new CPU designs optimised for AI workloads and new GPUs, as well as software tools to ease the development of chatbots and other AI apps on Arm chips.

But the real gamechanger is how these products are delivered. Historically, Arm provided specs or abstract designs that chipmakers had to translate into physical blueprints – an immense challenge arranging billions of transistors.

For this latest offering, Arm collaborated with Samsung and TSMC to provide physical chip blueprints ready for manufacturing, which was a huge time saver.

Samsung’s Jongwook Kye praised the partnership, stating their 3nm process combined with Arm’s CPU solutions meets soaring demand for generative AI in mobiles through “early and tight collaboration” in the areas of DTCO and PPA maximisation for an on-time silicon delivery that hit performance and efficiency demands.

TSMC’s head of the ecosystem and alliance management division, Dan Kochpatcharin echoed this, calling the AI-optimised CSS “a prime example” of Arm-TSMC collaboration helping designers push semiconductor innovation’s boundaries for unmatched AI performance and efficiency.

“Together with Arm and our Open Innovation Platform® (OIP) ecosystem partners, we empower our customers to accelerate their AI innovation using the most advanced process technologies and design solutions,” Kochpatcharin emphasised.

Arm isn’t trying to compete with customers, but rather enable faster time-to-market by providing optimised designs for neural processors delivering cutting-edge AI performance.

As Arm’s Chris Bergey said, “We’re combining a platform where these accelerators can be very tightly coupled” to customer NPUs.

Essentially, Arm provides more refined, “baked” designs customers can integrate with their own accelerators to rapidly develop powerful AI-driven chips and devices.

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Gemini 1.5 Flash is a new addition to Google’s family of models, designed to be faster and more efficient to serve at scale. While lighter-weight than the 1.5 Pro, it retains the ability for multimodal reasoning across vast amounts of information and features the breakthrough long context window of one million tokens.

“1.5 Flash excels at summarisation, chat applications, image and video captioning, data extraction from long documents and tables, and more,” explained Demis Hassabis, CEO of Google DeepMind. “This is because it’s been trained by 1.5 Pro through a process called ‘distillation,’ where the most essential knowledge and skills from a larger model are transferred to a smaller, more efficient model.”

Meanwhile, Google has significantly improved the capabilities of its Gemini 1.5 Pro model, extending its context window to a groundbreaking two million tokens. Enhancements have been made to its code generation, logical reasoning, multi-turn conversation, and audio and image understanding capabilities.

The company has also integrated Gemini 1.5 Pro into Google products, including the Gemini Advanced and Workspace apps. Additionally, Gemini Nano now understands multimodal inputs, expanding beyond text-only to include images.

Google announced its next generation of open models, Gemma 2, designed for breakthrough performance and efficiency. The Gemma family is also expanding with PaliGemma, the company’s first vision-language model inspired by PaLI-3.

Finally, Google shared progress on Project Astra (advanced seeing and talking responsive agent), its vision for the future of AI assistants. The company has developed prototype agents that can process information faster, understand context better, and respond quickly in conversation.

“We’ve always wanted to build a universal agent that will be useful in everyday life. Project Astra, shows multimodal understanding and real-time conversational capabilities,” explained Google CEO Sundar Pichai.

“With technology like this, it’s easy to envision a future where people could have an expert AI assistant by their side, through a phone or glasses.”

Google says that some of these capabilities will be coming to its products later this year. Developers can find all of the Gemini-related announcements they need here.

See also: GPT-4o delivers human-like AI interaction with text, audio, and vision integration

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GPT-4o, where the “o” stands for “omni,” is designed to cater to a broader spectrum of input and output modalities. “It accepts as input any combination of text, audio, and image and generates any combination of text, audio, and image outputs,” OpenAI announced.

Users can expect a response time as quick as 232 milliseconds, mirroring human conversational speed, with an impressive average response time of 320 milliseconds.

Pioneering capabilities

The introduction of GPT-4o marks a leap from its predecessors by processing all inputs and outputs through a single neural network. This approach enables the model to retain critical information and context that were previously lost in the separate model pipeline used in earlier versions.

Prior to GPT-4o, ‘Voice Mode’ could handle audio interactions with latencies of 2.8 seconds for GPT-3.5 and 5.4 seconds for GPT-4. The previous setup involved three distinct models: one for transcribing audio to text, another for textual responses, and a third for converting text back to audio. This segmentation led to loss of nuances such as tone, multiple speakers, and background noise.

As an integrated solution, GPT-4o boasts notable improvements in vision and audio understanding. It can perform more complex tasks such as harmonising songs, providing real-time translations, and even generating outputs with expressive elements like laughter and singing. Examples of its broad capabilities include preparing for interviews, translating languages on the fly, and generating customer service responses.

Nathaniel Whittemore, Founder and CEO of Superintelligent, commented: “Product announcements are going to inherently be more divisive than technology announcements because it’s harder to tell if a product is going to be truly different until you actually interact with it. And especially when it comes to a different mode of human-computer interaction, there is even more room for diverse beliefs about how useful it’s going to be.

“That said, the fact that there wasn’t a GPT-4.5 or GPT-5 announced is also distracting people from the technological advancement that this is a natively multimodal model. It’s not a text model with a voice or image addition; it is a multimodal token in, multimodal token out. This opens up a huge array of use cases that are going to take some time to filter into the consciousness.”

Performance and safety

GPT-4o matches GPT-4 Turbo performance levels in English text and coding tasks but outshines significantly in non-English languages, making it a more inclusive and versatile model. It sets a new benchmark in reasoning with a high score of 88.7% on 0-shot COT MMLU (general knowledge questions) and 87.2% on the 5-shot no-CoT MMLU.

The model also excels in audio and translation benchmarks, surpassing previous state-of-the-art models like Whisper-v3. In multilingual and vision evaluations, it demonstrates superior performance, enhancing OpenAI’s multilingual, audio, and vision capabilities.

OpenAI has incorporated robust safety measures into GPT-4o by design, incorporating techniques to filter training data and refining behaviour through post-training safeguards. The model has been assessed through a Preparedness Framework and complies with OpenAI’s voluntary commitments. Evaluations in areas like cybersecurity, persuasion, and model autonomy indicate that GPT-4o does not exceed a ‘Medium’ risk level across any category.

Further safety assessments involved extensive external red teaming with over 70 experts in various domains, including social psychology, bias, fairness, and misinformation. This comprehensive scrutiny aims to mitigate risks introduced by the new modalities of GPT-4o.

Availability and future integration

Starting today, GPT-4o’s text and image capabilities are available in ChatGPT—including a free tier and extended features for Plus users. A new Voice Mode powered by GPT-4o will enter alpha testing within ChatGPT Plus in the coming weeks.

Developers can access GPT-4o through the API for text and vision tasks, benefiting from its doubled speed, halved price, and enhanced rate limits compared to GPT-4 Turbo.

OpenAI plans to expand GPT-4o’s audio and video functionalities to a select group of trusted partners via the API, with broader rollout expected in the near future. This phased release strategy aims to ensure thorough safety and usability testing before making the full range of capabilities publicly available.

“It’s hugely significant that they’ve made this model available for free to everyone, as well as making the API 50% cheaper. That is a massive increase in accessibility,” explained Whittemore.

OpenAI invites community feedback to continuously refine GPT-4o, emphasising the importance of user input in identifying and closing gaps where GPT-4 Turbo might still outperform.

(Image Credit: OpenAI)

See also: OpenAI takes steps to boost AI-generated content transparency

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For decades, the media has jumped on the big tech stories, including human-like robots that will do all the basic household chores for us. As far back as 1966, we were introduced to Mabel The Robot Housemaid, who was going to be doing all the tasks by 1976. While that failed to be a reality, AI has seamlessly integrated itself into all our lives, and while there might not be any Mables, many of us have assistants called Alexa, Siri, and Cortana.

These robots may not be able to do the ironing for us, but they can be used to turn the lights on and off, program the oven, or control our heating systems when we are not around. Rather than take over all the physical work, they help us in the background and are integrated into our homes. According to today’s experts, by 2033, robots will be doing almost 40% of our housework. This seems somewhat similar to the 1966 claims, but this is backed up by data from Japan’s Ochanomizu and the UK’s University of Oxford. 65 AI experts were asked to predict what everyday tasks will become automated within the next five to ten years.

The study looked at the question “what kind of futures are imagined for unpaid work? If robots take our jobs, will they at least also take out the trash for us?” It is suggested that the time people spend doing housework will decrease by 46% in the next decade. However, the biggest task that is likely to become more automated is grocery shopping. The experts predict that by 2033 almost 60% of our grocery shop will be performed by AI. However, it is unlikely that machines will be trusted with caring responsibilities such as looking after the elderly or children. Even if AI had the technical ability to undertake these tasks, the studies experts believe there would be acceptability issues of delegating childcare to machines due to potential developmental impacts on the child and privacy implications.

So, if AI is not looking after our children or doing the ironing, what tasks is it doing? Given the market size, this sector is a massive part of the global economy. The most recent statistics predict it will be worth US$ 184.00bn in 2024. However, that is a small fry compared to forecasts for 2030. The market is expected to grow at almost 29% and will be worth a staggering US$826 billion by the end of the decade.

Here are some areas where AI plays an integral part in our lives, so much so that we almost forget how we functioned before.

We open our phones with face IDs. It is AI that enables this functionality. Using biometrics, the device can see you in 3D and capture images of your face using 30,000 invisible infrared dots. Then, using machine learning algorithms, it compares the scan of your face with what it has stored on file to determine if it is you or an intruder trying to access your phone. Apple claims that the chance of fooling its FaceID is one in a million

Once our phones are open, there are many places we might choose to go. Some people head off to check social media or catch up on the news. Other people use their phones for entertainment, like online games, or to visit an online casino. AI and algorithms are integral to the functioning of these sites, with AI involved in everything from customer services to verifying payments and paying out winnings. Players get a personalised experience as the AI learns which games they enjoy playing, which means players can choose from the newest games that are on offer. However, rather than trawling through all the latest releases, the system can learn from what they have played before and offer them something similar to play next.

AI also updates social media feeds. What a user sees is personalised because the algorithm has learned what posts you react to based on your history. It makes friend suggestions and news posts. The next step for AI is to recognise better and, filter out misinformation, and prevent cyberbullying. Getting rid of fake news is even more crucial as 2024 is a global year of general elections.

We use spell check and other tools like Grammarly when we write on our computers and phones, whether to send emails, messages, or reports. These help us create error-free messages by using natural language processing and suggestions. More AI is involved when we send and receive messages with spam filters, blocking some emails and sending them to our junk boxes. In addition, anti-virus software employs machine learning to protect our email accounts and computers.

While these examples all happen behind the scenes, one of the most notable changes in recent years is our use of digital voice assistants. Whether we want to get directions or find out what the weather will be like, Siri, Alexa, Google Home, and Cortana accompany us wherever we go. They have become indispensable for many people who use them as a co-pilot when driving and a general source of endless information around the home. These assistants use natural language processors and generators driven by AI to answer all the questions. They are increasingly programmed to give ‘human-like’ responses and can even sound offended at times.

Since 1966, we have dreamed of robots doing the housework, and while that is not a reality, our homes are becoming increasingly ‘smart’. We have thermostats that allow us to control the heating from our phones and fridges that can create shopping lists based on what is no longer in the refrigerator. They can also recommend what you might like to buy as an accompaniment based on what is in your fridge, such as wine or condiments.

There is still no sign of Mabel, but maybe she will put in an appearance one of these days.

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According to two sources familiar with the matter who spoke to Reuters, OpenAI is scheduled to unveil its AI-powered search tool on Monday. The introduction of this product coincides closely with the timing of Google’s annual I/O conference, which starts on Tuesday and is anticipated to feature several AI-related announcements.

While Google remains a titan in search, it too has been adapting to incorporate AI more deeply into its functionalities. Google began trialling AI-powered search summaries in the US over a year ago and expanded testing to selected, signed-in UK users last month.

The potential entry of OpenAI into the search engine market adds a new layer of competition not only for Google, but also for other entities like Perplexity. This week, Perplexity announced a partnership with SoundHound to enhance voice assistants for IoT devices with its AI-powered search capabilities.

OpenAI, heavily supported by Microsoft, seems to be banking on the intersection of AI and search engine technology to carve out its niche. Microsoft previously integrated OpenAI’s AI capabilities into its Bing search engine and Edge browser in February 2023, making these advanced features available to paid subscribers, along with integration into its Microsoft Office suite.

OpenAI’s forthcoming search product is expected to expand on its existing flagship tool, ChatGPT. Reports from Bloomberg reveal that the new feature will allow users to pose questions to ChatGPT and receive responses that pull information from the web with appropriate citations. This could include references to Wikipedia or various blogs and might even provide illustrative images or diagrams relevant to the queries.

If OpenAI successfully launches this new search product, it could signify a significant shift in how internet searches are conducted—moving away from traditional search models towards more integrated, AI-driven responses that significantly enhance user experience.

(Photo by GR Stocks)

See also: Coalition of news publishers sue Microsoft and OpenAI

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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First reported by The Verge, the group of eight publications owned by Alden Global Capital (AGC) – including the Chicago Tribune, New York Daily News, and Orlando Sentinel – allege the companies have purloined “millions” of their articles without permission and without payment “to fuel the commercialisation of their generative artificial intelligence products, including ChatGPT and Copilot.”

The lawsuit is the latest legal action taken against Microsoft and OpenAI over their alleged misuse of copyrighted content to build large language models (LLMs) that power AI technologies like ChatGPT. In the complaint, the AGC publications claim the companies’ chatbots can reproduce their articles verbatim shortly after publication, without providing prominent links back to the original sources.

“This lawsuit is not a battle between new technology and old technology. It is not a battle between a thriving industry and an industry in transition. It is most surely not a battle to resolve the phalanx of social, political, moral, and economic issues that GenAI raises,” the complaint reads.

“This lawsuit is about how Microsoft and OpenAI are not entitled to use copyrighted newspaper content to build their new trillion-dollar enterprises without paying for that content.”

The plaintiffs also accuse the AI models of “hallucinations,” attributing inaccurate reporting to their publications. They reference OpenAI’s previous admission that it would be “impossible” to train today’s leading AI models without using copyrighted materials.

The allegations echo those made by The New York Times in a separate lawsuit filed last year. The Times claimed Microsoft and OpenAI used almost a century’s worth of copyrighted content to allow their AI to mimic its expressive style without a licensing agreement.

In seeking to dismiss key parts of the Times’ lawsuit, Microsoft accused the paper of “doomsday futurology” by suggesting generative AI could threaten independent journalism.

The AGC publications argue that OpenAI, now valued at $90 billion after becoming a for-profit company, and Microsoft – which has seen hundreds of billions of dollars added to its market value from ChatGPT and Copilot – are profiting from the unauthorised use of copyrighted works.

The news publishers are seeking unspecified damages and an order for Microsoft and OpenAI to destroy any GPT and LLM models utilising their copyrighted content.

Earlier this week, OpenAI signed a licensing partnership with The Financial Times to lawfully integrate the newspaper’s journalism. However, the latest lawsuit from AGC highlights the growing tensions between tech companies developing generative AI and content creators concerned about the unchecked use of their works to train profitable AI systems.

(Photo by Wesley Tingey)

See also: OpenAI faces complaint over fictional outputs

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