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On Monday, Apple debuted "Apple Intelligence," a new suite of free AI-powered features for iOS 18, iPadOS 18, macOS Sequoia that includes creating email summaries, generating images and emoji, and allowing Siri to take actions on your behalf. These features are achieved through a combination of on-device and cloud processing, with a strong emphasis on privacy. Apple says that Apple Intelligence features will be widely available later this year and will be available as a beta test for developers this summer.

The announcements came during a livestream WWDC keynote and a simultaneous event attended by the press on Apple's campus in Cupertino, California. In an introduction, Apple CEO Tim Cook said the company has been using machine learning for years, but the introduction of large language models (LLMs) presents new opportunities to elevate the capabilities of Apple products. He emphasized the need for both personalization and privacy in Apple's approach.

At last year's WWDC, Apple avoided using the term "AI" completely, instead preferring terms like "machine learning" as Apple's way of avoiding buzzy hype while integrating applications of AI into apps in useful ways. This year, Apple figured out a new way to largely avoid the abbreviation "AI" by coining "Apple Intelligence," a catchall branding term that refers to a broad group of machine learning, LLM, and image generation technologies. By our count, the term "AI" was used sparingly in the keynote—most notably near the end of the presentation when Apple executive Craig Federighi said, "It's AI for the rest of us."

Enlarge / The Google "G" logo surrounded by whimsical characters, all of which look stunned and surprised. (credit: Google)

On Thursday, Google capped off a rough week of providing inaccurate and sometimes dangerous answers through its experimental AI Overview feature by authoring a follow-up blog post titled, "AI Overviews: About last week." In the post, attributed to Google VP Liz Reid, head of Google Search, the firm formally acknowledged issues with the feature and outlined steps taken to improve a system that appears flawed by design, even if it doesn't realize it is admitting it.

To recap, the AI Overview feature—which the company showed off at Google I/O a few weeks ago—aims to provide search users with summarized answers to questions by using an AI model integrated with Google's web ranking systems. Right now, it's an experimental feature that is not active for everyone, but when a participating user searches for a topic, they might see an AI-generated answer at the top of the results, pulled from highly ranked web content and summarized by an AI model.

While Google claims this approach is "highly effective" and on par with its Featured Snippets in terms of accuracy, the past week has seen numerous examples of the AI system generating bizarre, incorrect, or even potentially harmful responses, as we detailed in a recent feature where Ars reporter Kyle Orland replicated many of the unusual outputs.

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On Thursday, several major tech companies, including Google, Intel, Microsoft, Meta, AMD, Hewlett-Packard Enterprise, Cisco, and Broadcom, announced the formation of the Ultra Accelerator Link (UALink) Promoter Group to develop a new interconnect standard for AI accelerator chips in data centers. The group aims to create an alternative to Nvidia's proprietary NVLink interconnect technology, which links together multiple servers that power today's AI applications like ChatGPT.

The beating heart of AI these days lies in GPUs, which can perform massive numbers of matrix multiplications—necessary for running neural network architecture—in parallel. But one GPU often isn't enough for complex AI systems. NVLink can connect multiple AI accelerator chips within a server or across multiple servers. These interconnects enable faster data transfer and communication between the accelerators, allowing them to work together more efficiently on complex tasks like training large AI models.

This linkage is a key part of any modern AI data center system, and whoever controls the link standard can effectively dictate which hardware the tech companies will use. Along those lines, the UALink group seeks to establish an open standard that allows multiple companies to contribute and develop AI hardware advancements instead of being locked into Nvidia's proprietary ecosystem. This approach is similar to other open standards, such as Compute Express Link (CXL)—created by Intel in 2019—which provides high-speed, high-capacity connections between CPUs and devices or memory in data centers.

Enlarge / When you do math on a computer, you fly through a numerical tunnel like this—figuratively, of course. (credit: Getty Images)

Computer scientists have discovered a new way to multiply large matrices faster than ever before by eliminating a previously unknown inefficiency, reports Quanta Magazine. This could eventually accelerate AI models like ChatGPT, which rely heavily on matrix multiplication to function. The findings, presented in two recent papers, have led to what is reported to be the biggest improvement in matrix multiplication efficiency in over a decade.

Multiplying two rectangular number arrays, known as matrix multiplication, plays a crucial role in today's AI models, including speech and image recognition, chatbots from every major vendor, AI image generators, and video synthesis models like Sora. Beyond AI, matrix math is so important to modern computing (think image processing and data compression) that even slight gains in efficiency could lead to computational and power savings.

Graphics processing units (GPUs) excel in handling matrix multiplication tasks because of their ability to process many calculations at once. They break down large matrix problems into smaller segments and solve them concurrently using an algorithm.

Enlarge (credit: Jaap Arriens/NurPhoto/Getty Images)

Wikipedia has downgraded tech website CNET's reliability rating following extensive discussions among its editors regarding the impact of AI-generated content on the site's trustworthiness, as noted in a detailed report from Futurism. The decision reflects concerns over the reliability of articles found on the tech news outlet after it began publishing AI-generated stories in 2022.

Around November 2022, CNET began publishing articles written by an AI model under the byline "CNET Money Staff." In January 2023, Futurism brought widespread attention to the issue and discovered that the articles were full of plagiarism and mistakes. (Around that time, we covered plans to do similar automated publishing at BuzzFeed.) After the revelation, CNET management paused the experiment, but the reputational damage had already been done.

Wikipedia maintains a page called "Reliable sources/Perennial sources" that includes a chart featuring news publications and their reliability ratings as viewed from Wikipedia's perspective. Shortly after the CNET news broke in January 2023, Wikipedia editors began a discussion thread on the Reliable Sources project page about the publication.

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On Wednesday, Google announced a new family of AI language models called Gemma, which are free, open-weights models built on technology similar to the more powerful but closed Gemini models. Unlike Gemini, Gemma models can run locally on a desktop or laptop computer. It's Google's first significant open large language model (LLM) release since OpenAI's ChatGPT started a frenzy for AI chatbots in 2022.

Gemma models come in two sizes: Gemma 2B (2 billion parameters) and Gemma 7B (7 billion parameters), each available in pre-trained and instruction-tuned variants. In AI, parameters are values in a neural network that determine AI model behavior, and weights are a subset of these parameters stored in a file.

Developed by Google DeepMind and other Google AI teams, Gemma pulls from techniques learned during the development of Gemini, which is the family name for Google's most capable (public-facing) commercial LLMs, including the ones that power its Gemini AI assistant. Google says the name comes from the Latin gemma, which means "precious stone."

Enlarge (credit: Benj Edwards / Getty Images)

On Tuesday, ChatGPT users began reporting unexpected outputs from OpenAI's AI assistant, flooding the r/ChatGPT Reddit sub with reports of the AI assistant "having a stroke," "going insane," "rambling," and "losing it." OpenAI has acknowledged the problem and is working on a fix, but the experience serves as a high-profile example of how some people perceive malfunctioning large language models, which are designed to mimic humanlike output.

ChatGPT is not alive and does not have a mind to lose, but tugging on human metaphors (called "anthropomorphization") seems to be the easiest way for most people to describe the unexpected outputs they have been seeing from the AI model. They're forced to use those terms because OpenAI doesn't share exactly how ChatGPT works under the hood; the underlying large language models function like a black box.

"It gave me the exact same feeling—like watching someone slowly lose their mind either from psychosis or dementia," wrote a Reddit user named z3ldafitzgerald in response to a post about ChatGPT bugging out. "It’s the first time anything AI related sincerely gave me the creeps."

Enlarge / The real Will Smith eating spaghetti, parodying an AI-generated video from 2023. (credit: Will Smith / Getty Images / Benj Edwards)

On Monday, Will Smith posted a video on his official Instagram feed that parodied an AI-generated video of the actor eating spaghetti that went viral last year. With the recent announcement of OpenAI's Sora video synthesis model, many people have noted the dramatic jump in AI-video quality over the past year compared to the infamous spaghetti video. Smith's new video plays on that comparison by showing the actual actor eating spaghetti in a comical fashion and claiming that it is AI-generated.

Captioned "This is getting out of hand!", the Instagram video uses a split screen layout to show the original AI-generated spaghetti video created by a Reddit user named "chaindrop" in March 2023 on the top, labeled with the subtitle "AI Video 1 year ago." Below that, in a box titled "AI Video Now," the real Smith shows 11 video segments of himself actually eating spaghetti by slurping it up while shaking his head, pouring it into his mouth with his fingers, and even nibbling on a friend's hair. 2006's Snap Yo Fingers by Lil Jon plays in the background.

In the Instagram comments section, some people expressed confusion about the new (non-AI) video, saying, "I'm still in doubt if second video was also made by AI or not." In a reply, someone else wrote, "Boomers are gonna loose [sic] this one. Second one is clearly him making a joke but I wouldn’t doubt it in a couple months time it will get like that."

Enlarge (credit: Reddit)

On Friday, Bloomberg reported that Reddit has signed a contract allowing an unnamed AI company to train its models on the site's content, according to people familiar with the matter. The move comes as the social media platform nears the introduction of its initial public offering (IPO), which could happen as soon as next month.

Reddit initially revealed the deal, which is reported to be worth $60 million a year, earlier in 2024 to potential investors of an anticipated IPO, Bloomberg said. The Bloomberg source speculates that the contract could serve as a model for future agreements with other AI companies.

After an era where AI companies utilized AI training data without expressly seeking any rightsholder permission, some tech firms have more recently begun entering deals where some content used for training AI models similar to GPT-4 (which runs the paid version of ChatGPT) comes under license. In December, for example, OpenAI signed an agreement with German publisher Axel Springer (publisher of Politico and Business Insider) for access to its articles. Previously, OpenAI has struck deals with other organizations, including the Associated Press. Reportedly, OpenAI is also in licensing talks with CNN, Fox, and Time, among others.