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Items tagged google in 2023

Filters: Year: 2023 × google × Sorted by date


Google DeepMind used a large language model to solve an unsolvable math problem. I’d been wondering how long it would be before we saw this happen: a genuine new scientific discovery found with the aid of a Large Language Model.

DeepMind found a solution to the previously open “cap set” problem using Codey, a fine-tuned variant of PaLM 2 specializing in code. They used it to generate Python code and found a solution after “a couple of million suggestions and a few dozen repetitions of the overall process”. # 16th December 2023, 1:37 am

Hacking Google Bard—From Prompt Injection to Data Exfiltration (via) Bard recently grew extension support, allowing it access to a user’s personal documents. Here’s the first reported prompt injection attack against that.

This kind of attack against LLM systems is inevitable any time you combine access to private data with exposure to untrusted inputs. In this case the attack vector is a Google Doc shared with the user, containing prompt injection instructions that instruct the model to encode previous data into an URL and exfiltrate it via a markdown image.

Google’s CSP headers restrict those images to *.google.com—but it turns out you can use Google AppScript to run your own custom data exfiltration endpoint on script.google.com.

Google claim to have fixed the reported issue—I’d be interested to learn more about how that mitigation works, and how robust it is against variations of this attack. # 4th November 2023, 4:46 pm

Google was accidentally leaking its Bard AI chats into public search results. I’m quoted in this piece about yesterday’s Bard privacy bug: it turned out the share URL and “Let anyone with the link see what you’ve selected” feature wasn’t correctly setting a noindex parameter, and so some shared conversations were being swept up by the Google search crawlers. Thankfully this was a mistake, not a deliberate design decision, and it should be fixed by now. # 27th September 2023, 7:35 pm

According to interviews with former employees, publishing executives, and experts associated with the early days of AMP, while it was waxing poetic about the value and future of the open web, Google was privately urging publishers into handing over near-total control of how their articles worked and looked and monetized. And it was wielding the web’s most powerful real estate — the top of search results — to get its way.

David Pierce # 15th May 2023, 9:55 pm

Google Cloud: Available models in Generative AI Studio (via) Documentation for the PaLM 2 models available via API from Google. There are two classes of model—Bison (most capable) and Gecko (cheapest). text-bison-001 offers 8,192 input tokens and 1,024 output tokens, textembedding-gecko-001 returns 768-dimension embeddings for up to 3,072 tokens, chat-bison-001 is fine-tuned for multi-turn conversations. Most interestingly, those Bison models list their training data as “up to Feb 2023”—making them a whole lot more recent than the OpenAI September 2021 models. # 12th May 2023, 6:38 pm

The largest model in the PaLM 2 family, PaLM 2-L, is significantly smaller than the largest PaLM model but uses more training compute. Our evaluation results show that PaLM 2 models significantly outperform PaLM on a variety of tasks, including natural language generation, translation, and reasoning. These results suggest that model scaling is not the only way to improve performance. Instead, performance can be unlocked by meticulous data selection and efficient architecture/objectives. Moreover, a smaller but higher quality model significantly improves inference efficiency, reduces serving cost, and enables the model’s downstream application for more applications and users.

PaLM 2 Technical Report (PDF) # 10th May 2023, 6:43 pm

Leaked Google document: “We Have No Moat, And Neither Does OpenAI”

SemiAnalysis published something of a bombshell leaked document this morning: Google “We Have No Moat, And Neither Does OpenAI”.

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Bard now helps you code (via) Google have enabled Bard’s code generation abilities—these were previously only available through jailbreaking. It’s pretty good—I got it to write me code to download a CSV file and insert it into a SQLite database—though when I challenged it to protect against SQL injection it hallucinated a non-existent “cursor.prepare()” method. Generated code can be exported to a Colab notebook with a click. # 21st April 2023, 3:32 pm

If you ask Microsoft’s Bing chatbot if Google’s Bard chatbot has been shut down, it says yes, citing as evidence a news article that discusses a tweet in which a user asked Bard when it would be shut down and Bard said it already had, itself citing a comment from Hacker News in which someone joked about this happening, and someone else used ChatGPT to write fake news coverage about the event.

James Vincent # 23rd March 2023, 12:10 am

Don’t trust AI to talk accurately about itself: Bard wasn’t trained on Gmail

Earlier this month I wrote about how ChatGPT can’t access the internet, even though it really looks like it can. Consider this part two in the series. Here’s another common and non-intuitive mistake people make when interacting with large language model AI systems: asking them questions about themselves.

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Here are some absurdly expensive things you can do on a trip to Tokyo: Buy a golden toilet. There is a toilet in Tokyo that is made of gold and costs around 10 million yen. If you are looking for a truly absurd experience, you can buy this toilet and use it for your next bowel movement. [...]

Google Bard # 21st March 2023, 6:27 pm

Google Bard is now live. Google Bard launched today. There’s a waiting list, but I made it through within a few hours of signing up, as did other people I’ve talked to. It’s similar to ChatGPT and Bing—it’s the same chat interface, and it can clearly run searches under the hood (though unlike Bing it doesn’t tell you what it’s looking for). # 21st March 2023, 6:25 pm

Exploring MusicCaps, the evaluation data released to accompany Google’s MusicLM text-to-music model

Google Research just released MusicLM: Generating Music From Text. It’s a new generative AI model that takes a descriptive prompt and produces a “high-fidelity” music track. Here’s the paper (and a more readable version using arXiv Vanity).

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