Editor’s Pick

In 2017, eight machine-learning researchers at Google released a groundbreaking research paper called Attention Is All You Need, which introduced the Transformer AI architecture that underpins almost all of today’s high-profile generative AI models.

The Transformer has made a key component of the modern AI boom possible by translating (or transforming, if you will) input chunks of data called “tokens” into another desired form of output using a neural network. Variations of the Transformer architecture power language models like GPT-4o (and ChatGPT), audio synthesis models that run Google’s NotebookLM and OpenAI’s Advanced Voice Mode, video synthesis models like Sora, and image synthesis models like Midjourney.

At TED AI 2024 in October, one of those eight researchers, Jakob Uszkoreit, spoke with Ars Technica about the development of transformers, Google’s early work on large language models, and his new venture in biological computing.

Read full article

Comments

There’s a general consensus that we won’t be able to consistently perform sophisticated quantum calculations without the development of error-corrected quantum computing, which is unlikely to arrive until the end of the decade. It’s still an open question, however, whether we could perform limited but useful calculations at an earlier point. IBM is one of the companies that’s betting the answer is yes, and on Wednesday, it announced a series of developments aimed at making that possible.

On their own, none of the changes being announced are revolutionary. But collectively, changes across the hardware and software stacks have produced much more efficient and less error-prone operations. The net result is a system that supports the most complicated calculations yet on IBM’s hardware, leaving the company optimistic that its users will find some calculations where quantum hardware provides an advantage.

Better hardware and software

IBM’s early efforts in the quantum computing space saw it ramp up the qubit count rapidly, being one of the first companies to reach the 1,000 qubit count. However, each of those qubits had an error rate that ensured that any algorithms that tried to use all of these qubits in a single calculation would inevitably trigger one. Since then, the company’s focus has been on improving the performance of smaller processors. Wednesday’s announcement was based on the introduction of the second version of its Heron processor, which has 133 qubits. That’s still beyond the capability of simulations on classical computers, should it be able to operate with sufficiently low errors.

Read full article

Comments

On Friday, research organization Epoch AI released FrontierMath, a new mathematics benchmark that has been turning heads in the AI world because it contains hundreds of expert-level problems that leading AI models solve less than 2 percent of the time, according to Epoch AI. The benchmark tests AI language models (such as GPT-4o, which powers ChatGPT) against original mathematics problems that typically require hours or days for specialist mathematicians to complete.

FrontierMath’s performance results, revealed in a preprint research paper, paint a stark picture of current AI model limitations. Even with access to Python environments for testing and verification, top models like Claude 3.5 Sonnet, GPT-4o, o1-preview, and Gemini 1.5 Pro scored extremely poorly. This contrasts with their high performance on simpler math benchmarks—many models now score above 90 percent on tests like GSM8K and MATH.

The design of FrontierMath differs from many existing AI benchmarks because the problem set remains private and unpublished to prevent data contamination. Many existing AI models are trained on other test problem datasets, allowing the AI models to easily solve the problems and appear more generally capable than they actually are. Many experts cite this as evidence that current large language models (LLMs) are poor generalist learners.

Read full article

Comments

In the short-term, the most dangerous thing about AI language models may be their ability to emotionally manipulate humans if not carefully conditioned. The world saw its first taste of that danger in February 2023 with the launch of Bing Chat, now called Microsoft Copilot.

During its early testing period, the temperamental chatbot gave the world a preview of an “unhinged” version of OpenAI’s GPT-4 prior to its official release. Sydney’s sometimes uncensored and “emotional” nature (including use of emojis) arguably gave the world its first large-scale encounter with a truly manipulative AI system. The launch set off alarm bells in the AI alignment community and served as fuel for prominent warning letters about AI dangers.

On November 19 at 4 pm Eastern (1 pm Pacific), Ars Technica Senior AI Reporter Benj Edwards will host a livestream conversation on YouTube with independent AI researcher Simon Willison that will explore the impact and fallout of the 2023 fiasco. We’re calling it “Bing Chat: Our First Encounter with Manipulative AI.”

Read full article

Comments

A few months ago, Anthropic quietly hired its first dedicated “AI welfare” researcher, Kyle Fish, to explore whether future AI models might deserve moral consideration and protection, reports AI newsletter Transformer. While sentience in AI models is an extremely controversial and contentious topic, the hire could signal a shift toward AI companies examining ethical questions about the consciousness and rights of AI systems.

Fish joined Anthropic’s alignment science team in September to develop guidelines for how Anthropic and other companies should approach the issue. The news follows a major report co-authored by Fish before he landed his Anthropic role. Titled “Taking AI Welfare Seriously,” the paper warns that AI models could soon develop consciousness or agency—traits that some might consider requirements for moral consideration. But the authors do not say that AI consciousness is a guaranteed future development.

“To be clear, our argument in this report is not that AI systems definitely are—or will be—conscious, robustly agentic, or otherwise morally significant,” the paper reads. “Instead, our argument is that there is substantial uncertainty about these possibilities, and so we need to improve our understanding of AI welfare and our ability to make wise decisions about this issue. Otherwise there is a significant risk that we will mishandle decisions about AI welfare, mistakenly harming AI systems that matter morally and/or mistakenly caring for AI systems that do not.”

Read full article

Comments

Anthropic has announced a partnership with Palantir and Amazon Web Services to bring its Claude AI models to unspecified US intelligence and defense agencies. Claude, a family of AI language models similar to those that power ChatGPT, will work within Palantir’s platform using AWS hosting to process and analyze data. But some critics have called out the deal as contradictory to Anthropic’s widely-publicized “AI safety” aims.

On X, former Google co-head of AI ethics Timnit Gebru wrote of Anthropic’s new deal with Palantir, “Look at how they care so much about ‘existential risks to humanity.'”

The partnership makes Claude available within Palantir’s Impact Level 6 environment (IL6), a defense-accredited system that handles data critical to national security up to the “secret” classification level. This move follows a broader trend of AI companies seeking defense contracts, with Meta offering its Llama models to defense partners and OpenAI pursuing closer ties with the Defense Department.

Read full article

Comments

Broadcom has a new subscription tier for VMware virtualization software that may appease some disgruntled VMware customers, especially small to medium-sized businesses. The new VMware vSphere Enterprise Plus subscription tier creates a more digestible bundle that’s more appropriate for smaller customers. But it may be too late to convince some SMBs not to abandon VMware.

Soon after Broadcom bought VMware, it stopped the sale of VMware perpetual licenses and started requiring subscriptions. Broadcom also bundled VMware’s products into a smaller number of SKUs, resulting in higher costs and frustration for customers that felt like they were being forced to pay for products that they didn’t want. All that, combined with Broadcom ditching some smaller VMware channel partners (and reportedly taking the biggest clients direct), have raised doubts that Broadcom’s VMware would be a good fit for smaller customers.

“The challenge with much of the VMware by Broadcom changes to date and before the announcement [of the vSphere Enterprise Plus subscription tier] is that it also forced many organizations to a much higher offering and much more components to a stack that they were previously uninterested in deploying,” Rick Vanover, Veeam’s product strategy VP, told Ars.

Read full article

Comments

Matter, the smart home standard that promises an interoperable future for home automation, even if it’s scattered and a bit buggy right now, is out with a new version, 1.4. It promises more device types, improvements for working across ecosystems, and tools for managing battery backups, solar panels, and heat pumps.

“Enhanced Multi-Admin” is the headline feature for anybody invested in Matter’s original promise, one where you can buy a device and it doesn’t matter if your other gear is meant for Amazon (Alexa), Google, Apple, or whatever, it should just connect and work. With 1.4, a home administrator should be able to let a device onto their network just once, and then have that device picked up by whatever controller they’re using. There have technically been ways for a device to be set up on, say, Alexa and Apple Home, but the process has been buggy, involves generating “secondary codes,” and is kind of an unpaid junior sysadmin job.

What’s now available is “Fabric Sync,” which sounds like something that happens in a static-ridden dryer. But “Fabrics” is how the Connectivity Standards Alliance (CSA) describes smart home systems, like Alexa or Google Home. In theory, with every tech company doing their best, you’d set up a smart light bulb with your iPhone, add it to your Apple Home, but still have it be able to be added to a Google Home system, Android phones included. Even better, ecosystems that don’t offer controls for entire categories, like Apple and smart displays (because it doesn’t make any), should still be able to pick up and control them.

Read full article

Comments

An international coalition of police agencies has taken a major whack at criminals accused of running a host of online scams, including phishing, the stealing of account credentials and other sensitive data, and the spreading of ransomware, Interpol said recently.

The operation, which ran from the beginning of April through the end of August, resulted in the arrest of 41 people and the takedown of 1,037 servers and other infrastructure running on 22,000 IP addresses. Synergia II, as the operation was named, was the work of multiple law enforcement agencies across the world, as well as three cybersecurity organizations.

A global response

“The global nature of cybercrime requires a global response which is evident by the support member countries provided to Operation Synergia II,” Neal Jetton, director of the Cybercrime Directorate at INTERPOL, said. “Together, we’ve not only dismantled malicious infrastructure but also prevented hundreds of thousands of potential victims from falling prey to cybercrime. INTERPOL is proud to bring together a diverse team of member countries to fight this ever-evolving threat and make our world a safer place.”

Read full article

Comments

On Wednesday, OpenAI CEO Sam Altman merely tweeted “chat.com,” announcing that the company had acquired the short domain name, which now points to the company’s ChatGPT AI assistant when visited in a web browser. As of Thursday morning, “chatgpt.com” still hosts the chatbot, with the new domain serving as a redirect.

The new domain name comes with an interesting backstory that reveals a multimillion-dollar transaction. HubSpot founder and CTO Dharmesh Shah purchased chat.com for $15.5 million in early 2023, The Verge reports. Shah sold the domain to OpenAI for an undisclosed amount, though he confirmed on X that he “doesn’t like profiting off of people he considers friends” and that he received payment in company shares by revealing he is “now an investor in OpenAI.“

As The Verge’s Kylie Robison points out, Shah originally bought the domain to promote conversational interfaces. “The reason I bought chat.com is simple: I think Chat-based UX (#ChatUX) is the next big thing in software. Communicating with computers/software through a natural language interface is much more intuitive. This is made possible by Generative A.I.,” Shah wrote in a LinkedIn post during his brief ownership.

Read full article

Comments