GenAI Weekly — Edition 19
Your Weekly Dose of Gen AI: News, Trends, and Breakthroughs
Stay at the forefront of the Gen AI revolution with Gen AI Weekly! Each week, we curate the most noteworthy news, insights, and breakthroughs in the field, equipping you with the knowledge you need to stay ahead of the curve.
Apple intelligence and AI maximalism
To begin, then: Apple has built an LLM with no chatbot. Apple has built its own foundation models, which (on the benchmarks it published) are comparable to anything else on the market, but there’s nowhere that you can plug a raw prompt directly into the model and get a raw output back - there are always sets of buttons and options shaping what you ask, and that’s presented to the user in different ways for different features. In most of these features, there’s no visible bot at all. You don’t ask a question and get a response: instead, your emails are prioritised, or you press ‘summarise’ and a summary appears. You can type a request into Siri (and Siri itself is only one of the many features using Apple’s models), but even then you don’t get raw model output back: you get GUI. The LLM is abstracted away as an API call.
My take on this: “No visible bot” is the best bot, as developed by Apple.
WWDC 2024: Apple Intelligence
An oft-told story is that back in 2009?—?two years after Dropbox debuted, two years before Apple unveiled iCloud?—?Steve Jobs invited Dropbox cofounders Drew Houston and Arash Ferdowsi to Cupertino to pitch them on selling the company to Apple. Dropbox, Jobs told them, was “a feature, not a product”.
It’s easy today to forget just how revolutionary a product Dropbox was. A simple installation on your Mac and boom, you had a folder that synced between every Mac you used?—?automatically, reliably, and quickly. At the time Dropbox had a big sign in its headquarters that read, simply, “It Just Works”, and they delivered on that ideal?—?at a time when no other sync service did. Jobs, of course, was trying to convince Houston and Ferdowsi to sell, but that doesn’t mean he was wrong that, ultimately, it was a feature, not a product. A tremendously useful feature, but a feature nonetheless.
Leading up to WWDC last week, I’d been thinking that this same description applies, in spades, to LLM generative AI. Fantastically useful, downright amazing at times, but features. Not products. Or at least not broadly universal products. Chatbots are products, of course. People pay for access to the best of them, or for extended use of them. But people pay for Dropbox too.
Chatbots can be useful. There are people doing amazing work through them. But they’re akin to the terminal and command-line tools. Most people just don’t think like that.
What Apple unveiled last week with Apple Intelligence wasn’t so much new products, but new features?—?a slew of them?—?for existing products, powered by generative AI.
My take on this: This is a great argument—that Apple is treating AI as a feature, not a product.
Google’s Gemma 2 to be available to researchers and developers through Vertex AI
Google says Gemma 2, its open lightweight model series, will be available to researchers and developers through Vertex AI starting next month. But while it initially only contained a 27-billion parameter member, the company surprised us by also including a 9-billion one.
Gemma 2 was introduced back in May at Google I/O as the successor to Gemma’s 2-billion and 7-billion parameter models, which debuted in February. The next-gen Gemma model is designed to run on Nvidia’s latest GPUs or a single TPU host in Vertex AI. It targets developers who want to incorporate AI into their apps or edge devices such as smartphones, IoT devices, and personal computers.
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An internal OpenAI model dubbed CriticGPT is much better than humans at catching coding bugs
OpenAI developed a new model by fine-tuning its most powerful offering, GPT-4, to assist human trainers tasked with assessing code. The company found that the new model, dubbed CriticGPT, could catch bugs that humans missed, and that human judges found its critiques of code to be better 63 percent of the time. OpenAI will look at extending the approach to areas beyond code in the future.
“We’re starting work to integrate this technique into our RLHF chat stack,” McAleese says. He notes that the approach is imperfect, since CriticGPT can also make mistakes by hallucinating, but he adds that the technique could help make OpenAI’s models as well as tools like ChatGPT more accurate by reducing errors in human training. He adds that it might also prove crucial in helping AI models become much smarter, because it may allow humans to help train an AI that exceeds their own abilities. “And as models continue to get better and better, we suspect that people will need more help,” McAleese says.
My take on this: This is an example of boring work that AI should be good at doing. A WWDC 2003 audience member’s ask is finally coming true.
See Also:
Amazon Is Investigating Perplexity Over Claims of Web Scraping Abuse
“AWS’s terms of service prohibit abusive and illegal activities and our customers are responsible for complying with those terms," Neighorn said in a statement. “We routinely receive reports of alleged abuse from a variety of sources and engage our customers to understand those reports.”
Scrutiny of Perplexity’s practices follows a June 11 report from Forbes that accused the startup of stealing at least one of its articles. WIRED investigations confirmed the practice and found further evidence of scraping abuse and plagiarism by systems linked to Perplexity’s AI-powered search chatbot. Engineers for Condé Nast, WIRED’s parent company, block Perplexity’s crawler across all its websites using a robots.txt file. But WIRED found the company had access to a server using an unpublished IP address—44.221.181.252—which visited Condé Nast properties at least hundreds of times in the past three months, apparently to scrape Condé Nast websites.
The machine associated with Perplexity appears to be engaged in widespread crawling of news websites that forbid bots from accessing their content. Spokespeople for The Guardian, Forbes, and The New York Times also say they detected the IP address repeatedly visiting their servers.
My take on this: The thing about the Internet is that the rules around scraping are simply a “gentleman’s agreement” with no enforcement.
Not all ‘open source’ AI models are actually open: here’s a ranking
Technology giants such as Meta and Microsoft are describing their artificial intelligence (AI) models as ‘open source’ while failing to disclose important information about the underlying technology, say researchers who analysed a host of popular chatbot models.
The definition of open source when it comes to AI models is not yet agreed, but advocates say that ’full’ openness boosts science, and is crucial for efforts to make AI accountable. What counts as open source is likely to take on increased importance when the European Union’s Artificial Intelligence Act comes into force. The legislation will apply less strict regulations to models that are classed as open.
Some big firms are reaping the benefits of claiming to have open-source models, while trying “to get away with disclosing as little as possible”, says Mark Dingemanse, a language scientist at Radboud University in Nijmegen, the Netherlands. This practice is known as open-washing.
“To our surprise, it was the small players, with relatively few resources, that go the extra mile,” says Dingemanse, who together with his colleague Andreas Liesenfeld, a computational linguist, created a league table that identifies the most and least open models (see table). They published their findings on 5 June in the conference proceedings of the 2024 ACM Conference on Fairness, Accountability and Transparency1.
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4 个月The part about multimodal models and their potential in transforming industries is super insightful