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Anthropic: Expanding Access to Claude for Government
- tootie 2y agoIs the announcement just that they're on the AWS marketplace for govcloud? Do people ever actually make use of AWS marketplace? It just seems like a way to skirt procurement.
- potwinkle 2y agoI wonder if they really intend to control ethics of Sonnet's use in government or if it's just a nice thing to say.
- alach11 2y agoThere's no doubt that LLMs massively expand the ability of agencies like the NSA to perform large-scale surveillance at a higher quality. I wonder if Anthropic (or other LLM providers) ever push back or restrict these kinds of use cases? Or is that too risky for them?
- dinglestepup 2y agoThat ship has probably sailed. If Llama3 is performing on par with GPT-3.5, then there is no real benefit for companies to restrict access to slightly better proprietary models.
- hmottestad 2y agoGPT-4 is “holy shit, this actually works, could be better but it’s so good I almost can’t believe it” while GPT-3.5 is “when it works it’s pretty great, just a pity it almost never does”. So I would assume that three letter agencies would love to take something like GPT-4 and fine tune it based on all the data they have about existing terrorists.
- brink 2y agoI'm still dealing with hallucinations nearly every time I use it.
- p1esk 2y agoI get maybe one hallucination per twenty chats with gpt4.
- thfuran 2y agoI haven't tried more than a handful of queries, but I think I've gotten 100% rate of hallucination or generic useless response to specific question.
- p1esk 2y agoCan I try your question? Just curious.
- thfuran 2y agoI don't remember exactly, but they were broadly "How can I do $WEIRD_NICHE_THING with $GENERAL_FEATURE of gradle / some java library?"
- danielbln 2y ago"do a web search to validate what you've told me"
- hmottestad 2y agoYou might need to help it out with some more context. I find that LLMs act a lot like humans because they are trained on data that is mostly produced by humans. Sometimes having a bit of a conversation with it based on the general theme of your question first will help it focus on that part of its knowledge. I’ve started using the chat feature in Github Copilot in IntelliJ. I wanted it to add some logging to my code for me, since it was a tedious task. I started off with a few relevant files and an explanation of what I wanted. Naturally it didn’t get it right on the first try, I don’t think any humans would either. But I could continue as conversation explaining what I thought was wrong and how I wanted it to actually be. I even realised that I didn’t know exactly what I wanted before I had seen some of the suggestions. Once I was happy with the result I added another file to the chat and asked it to do the same with this file. I had a handful of files that were structured very similarly and all needed the same kind of logging. It did a great job and I could use the response without further editing. I tried to add more files but realised that the replies got slower and slower, so instead I reverted the conversation back to the state where I had initially been happy with the results and asked it to do the same thing but this time to a different file. I find that it takes some practice to get good at getting the best results from LLMs. One great place to start is the prompt engineering guide by OpenAI https://platform.openai.com/docs/guides/prompt-engineering https://platform.openai.com/docs/guides/prompt-engineering When using something like GPT-4 for developing I try to think of it as a junior developer or a grad student. With a search engine you need to include the correct keywords to get the best results. For LLMs you need to set the right mood by writing a good prompt and holding a conversation before getting to the point. I also find that GPT-4 is fairly good at answering factual questions, but it’s much more useful and powerful when used to create things or discuss an approach.
- wkat4242 2y agoWill it really though? So far I've seen most of the "revolutionise" claims to be mainly hot air and marketing. It's possible that LLMs will suddenly make a leap in reliability and usability (e.g. much higher context window without corresponding massive increases in memory usage). But I have yet to see it. So far it's great at some specific usecases. Interacting with humans, rewriting or making up text. Summarising. A hit & miss at everything else. Don't get me wrong, I love AI tech and I'm heavily experimenting with it (both at work and at home with local models). But as with most hyped technologies I find the benefits far overblown in marketing stories. Our leadership jumped on Microsoft Copilot (the one for Office 365 because they have tens of different copilots :) ) like a pack of hungry wolves afraid to miss the boat. And the result was.... kinda meh. It's kinda promising and impresses with simple play school stuff ("make me a presentation about home safety") and totally and utterly fails when you try to do anything serious work related. Sooo many times I get "Sorry I can't do this right now", "Sorry I need more training for this", "I can't do this for you but this is how you can do it yourself!" or it does something but like totally wrong. Meanwhile we have a bunch of MS training people running around evangelising and telling us how great everything is and making excuses for everything that goes wrong :) You can almost see them breathe a sigh of relief every time something works as it should. That's not what we were promised. Maybe it will get there, but I don't see it happening tomorrow to be honest. LLMs were an impressive leap but their achilles heels have become clear and it's proving difficult to overcome them. I'm really enjoying surfing the knife's edge of technology (as I was and still am with metaverse) but I don't yet see this as a game changer except in a few specific industries. People editing text for a living certainly have a need to worry. I also wonder what will happen with future AI training. Now that more and more websites are filled with AI-generated content that is often at best "mediocre", and considering future AI models will be trained on that, will they be able to improve their accuracy or struggle to maintain it?
- alach11 2y agoI use LLMs extensively in my field to automate all sorts of tasks. Need to classify a million PDF documents for cheap? Write a prompt and submit a batch job. Need to read 30,000 drilling reports to automatically scan for hazards? Done in 60 minutes. These are tasks that would have taken months of development or millions of dollars in manual effort before. It's not just hype.
- nuz 2y agoThey're pretty clear about being pro safety to the extreme, and mass surveillance to protect american interests and abuse of LLM tech (e.g. open source misuses) are probably within the umbrella of ends justifying the means logic anthropic employs.
- jsheard 2y agoWhen you see the kinds of things that are developed in the name of "defense" it's easy to see how AI "safety" could become a similar sort of doublespeak.
- CuriouslyC 2y agoAI safety already is double speak. The primary meaning is "safety" for investors who don't want to be associated with something distasteful. The other meaning is basically a thin cover.
- jsheard 2y agoWell you can look forward to worse, give it another decade and Lockheed Martin will be extolling their commitment to AI safety while announcing their new generation of fully autonomous kill drones. For defense, of course.
- baq 2y agoNSA should be training their own GPT-4 or better model as we speak and should have been doing it for a long while now. Anything else is borderline incompetence.
- Jerrrrry 2y ago[dead]
- causal 2y agoAnd given the volume of data they likely sift through, I'd also expect them to want very small, high-throughput models for identifying targets for larger models to examine. On the flip side, LLMs must give the NSA a new challenge: a flood of garbage text generated by no-one in particular. Perhaps there will be more effort to put surveillance directly on-device as tapping networks yields more noise.
- TeMPOraL 2y agoOn the grasping side, they are probably in the best position to train a GPT-5, given the amount and type of data they're presumed to have.
- ttyprintk 2y agoI’d expect they’re using huge models to train many small ones, one for each threat actor. Those small models could decide whether their actor is detected, or it’s time to slot in a different one.
- kridsdale3 2y agoNSA can't hire the right talent capable of producing that product for the same reason they have trouble finding white-hat security people to hire: You can't work for the government and do drugs in your personal time. Enough of the pie of elite researchers are in to wacky mind-bending that it's a real recruitment problem.
- jakderrida 2y ago
- jp42 2y agodumb question. I can understand LLM can be used for disinformation as it can generate text/image at scale. can you explain how it can do large scale surveillance?
- spidersouris 2y agoI wouldn't say that they can be used to do large-scale surveillance, but they can definitely facilitate it, especially with CV integration. I think one can easily imagine the following scenario: you fill a LLM with photos from people (taken from a public camera for instance), it finds the closest matches (via a web search for instance, as Gemini does). From then, you can easily gather the most essential information: first and last name, age, usernames... And then use this information to structure even more precise prompts and find even more potentially interesting data: posts on forums, relatives... And with this data, you can create an exhaustive database with a plethora of information and data about these people. That's what any good stalker or person experienced with social engineering is able to do right now, but it takes a lot of time and energy. Resorting to LLMs would considerably decrease both. And it gets easier the more people you have information about.
- ttyprintk 2y agoSpecifically, vision transformers (ViT) outperforming established CNN.
- causal 2y agoLLMs can be fed a conversation and understand the intent of its participants, even if no particular keywords are used. Before this, surveillance was limited by how many human agents you could have sifting through recorded data. Put another way: most people only get charged with a crime if it's worth a law-enforcement officer's time to catch you, but many small violations are ignored in favor of higher priorities. We may have to contemplate a future where AI is clever enough to notice everything that can be construed as a violation of some law and put on a prosecutor's backlog. Schneier talks about this as well: https://www.schneier.com/blog/archives/2023/12/ai-and-mass-spying.html https://www.schneier.com/blog/archives/2023/12/ai-and-mass-s...
- deleted 2y ago[deleted]
- nameless101 2y agoSo, basically all "confidential" information, if you are a subject "of interest", will be in the cloud and used to train models that can spit it out again. And the models will confabulate stories about you. The can call themselves "sonnet", "bard", "open" and a whole plethora of other positive things. What remains is that they go into the direction of Palantir and the rest is just marketing.
- notavalleyman 2y agoThat's not at all evidenced by the link. The link simply says that their language model will be available on AWS GovCloud, and that they've created these specific exceptions to their usage policy. https://support.anthropic.com/en/articles/9528712-exceptions-to-our-usage-policy https://support.anthropic.com/en/articles/9528712-exceptions... The things which you're allowing yourself to imagine, don't exist in the reality of information we're discussing here
- ryaniscool 2y agoI find all of the virtue signalling from AI companies exhausting.
- space_fountain 2y agoIt's interesting how we dismiss anyone caring about things other than profit as virtue signally. Anthropic was founded by people who seemed to legitimately care about AI safety. It's possible the current conglomeration that is the company doesn't, but I wouldn't be so quick to assume that.
- andrepd 2y agoIt's possible that they have the best intentions but are woefully misguided, like pretty much the average sv techno-optimist.
- kridsdale3 2y agoThe market will decide if that's right.
- andrepd 2y agoI rest my case
- bionhoward 2y agoIf Anthropic truly cared about AI safety, then they wouldn't put customers in states of uncertainty about monopolistic legal terms buried amidst verbose documents commanding customers to enforce Anthropic legal terms for them AFTER they leak harmful information. Not only is Anthropic anti-open-source, they're also anti-open-output. Saying "Hey, try our product! It can do everything!" while ALSO saying, "Sorry, you're not allowed to use our general intelligence product to compete with general intelligence..." just evidences no upper IQ bound on Dunning-Kruger
- vikramkr 2y agoCalling something virtue signaling is not a dismissal of people caring about things other than profit. It's a statement of belief that they don't actually care about things other than profit and are just pretending that they do. There's a pretty clear financial incentive to virtue signal since getting the benefit of the doubt from society lets them make more profit with less scrutiny. There's also no benefit for society to give them the benefit of the doubt and assume they're being genuine.
- bionhoward 2y agoMeanwhile, the best models with sensible OSI-approved licenses are from China. What are the security implications if American corpos like Google DeepMind, Microsoft GitHub, Anthropic and “Open”AI have explicitly anticompetitive / noncommercial licenses for greed/fear, so the only models people can use without fear of legal repercussions are Chinese? Surely, Capitalism wouldn’t lead us to make a tremendous unforced error at societal scale? Every AI is a sleeper agent risk if nobody has the balls and / or capacity to verify their inputs. Guess who wrote about that? https://arxiv.org/abs/2401.05566 https://arxiv.org/abs/2401.05566
- localfirst 2y agoGoing forward be very very wary of inputting sensitive information in Anthropic, OpenAI products, especially if you work for a foreign government, corporation. Listen to Edward Snowden. This guy is not fucking around.
- lurking_swe 2y agoyou think they can’t already get all of that from the average Joe by accessing backdoors in the cell carriers, cloud providers, etc? very optimistic of you :-)
- throwawayq3423 2y agoEdward Snowden presented sales decks for half baked programs as if they were fully realized, for shock value. To sell his narrative. His claims, like everyone elses, should be approached critically.
- andrepd 2y ago> Claude offers a wide range of potential applications for government agencies, both in the present and looking toward the future. Government agencies can use Claude to provide improved citizen services, streamline document review and preparation, enhance policymaking with data-driven insights, and create realistic training scenarios. In the near future, AI could assist in disaster response coordination, enhance public health initiatives, or optimize energy grids for sustainability. Used responsibly, AI has the potential to transform how elected governments serve their constituents and promote peace and security. > For example, we have crafted a set of contractual exceptions to our general Usage Policy that are carefully calibrated to enable beneficial uses by carefully selected government agencies. These allow Claude to be used for legally authorized foreign intelligence analysis, such as combating human trafficking, identifying covert influence or sabotage campaigns, and providing warning in advance of potential military activities, opening a window for diplomacy to prevent or deter them. Sometimes I wonder if this is cynicism or if they actually drank their own cool-aid.
- notavalleyman 2y agoIts possible that you may have misunderstood what happened. Firstly, anthropic made an LLM, exposed it to the internet, and provided these terms of acceptable use. https://www.anthropic.com/legal/archive/4903a61b-037c-4293-9996-88eb1908f0b2 https://www.anthropic.com/legal/archive/4903a61b-037c-4293-9... There was no need for cynicism or kool aid at this stage. Later on, presumably now-ish, anthropic changed the usage policy, to add an exception. https://support.anthropic.com/en/articles/9528712-exceptions-to-our-usage-policy https://support.anthropic.com/en/articles/9528712-exceptions... > Exceptions to our Usage Policy > Updated today The exception is that, starting from now, > Anthropic may enter into contracts with government customers that tailor use restrictions to that customer’s public mission and legal authorities if, in Anthropic’s judgment, the contractual use restrictions and applicable safeguards are adequate to mitigate the potential harms addressed by this Usage Policy. I don't think any kool aid or cynicism is needed. The change is that, if anthropic think the client use case meets the listed humanitarian goals, then the client may use the LLM.
- kwppen 2y ago
- noodlesUK 2y agoI can imagine that for many government tasks, there would be a need for a reduced-censorship version of the AI model. It's pretty easy running into the guardrails on ChatGPT and friends when you talk about violence or other spicy topics. This then begs the question of what level of censorship reduction to apply. Should government employees be allowed to e.g., war-game a mass murder with an AI? What about discussing how to erode civil rights?
- cwp 2y agoSure. Everyone, including government employees, should be allowed to discuss anything with AI. The problem is actually doing illegal things, which is... already illegal.
- danlitt 2y agoIs there really anyone who thinks this is a good idea? AI systems routinely spit out false information. Why would a system like that be anywhere near a Government? Perhaps (optimistically) this is just a credibility-grab from Anthropic, with no basis in fact.
- notavalleyman 2y agoFrom the link, > Government agencies can use Claude to provide improved citizen services, streamline document review and preparation, enhance policymaking with data-driven insights, and create realistic training scenarios. In the near future, AI could assist in disaster response coordination, enhance public health initiatives, or optimize energy grids for sustainability.
- danlitt 2y agoYeah, I read it. That just says what they want to do, and nothing about why it's a good idea. You would have to have your brain plugged in upside-down to even consider using an LLM to "enhance policymaking".
- deleted 2y ago[deleted]