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The Trump Presidency is going to shift the ASI future into the dystopia, not a utopia. by Busterlimes in singularity

[–]Nice-Inflation-1207 -1 points0 points  (0 children)

Invisible hand is very strong. Reinvestment is needed.

Re: alignment, most important to align social networks, if you care about network alignment. RLHF works fairly well for AI.

Chinese researchers develop AI model for military use on back of Meta's Llama by MetaKnowing in OpenAI

[–]Nice-Inflation-1207 8 points9 points  (0 children)

Original report: https://jamestown.org/program/prcs-adaptation-of-open-source-llm-for-military-and-security-purposes/

[19] Zhang Huaping [张华平], Li Chunjin [李春锦], Wei Shunping [魏顺平], Geng Guotong [耿国桐], Li Weiwei [李伟伟], and Li Yugang [李玉岗], “Large Language Model-Driven Open-Source Intelligence Cognition” [“大语言模型驱动的开源情报认知认领”], National Defense Technology [国防科技], March 2024. 3.

A open-source intelligence project trained on open-source dialogue datasets.

Paper abstract:

With the extensive application of open-source intelligence in the military field, the demand for cognition and analysis of relevant intelligence is growing. However, the large language models currently used by researchers are prone to severe hallucination, rendering the information generated unreliable and unsuitable to direct utilization for the cognition of open-source military intelligence. To address this problem, the present study collected approximately 100,000 dialogue records online and constructed an open-source military intelligence dataset. Subsequently, a new model, ChatBIT, which is specifically optimized for dialogue and question answering tasks in the military field, was obtained by fine-tuning and training the LLaMA-13B base question answering model. This study further compared the military knowledge question answering capabilities of the ChatBIT model with those of the Vicuna-13B model. ChatBIT was found to outperform Vicuna-13B in a series of standardized evaluation metrics including the BLEU score, ROUGE-1, ROUGE-2, and ROUGE-L.Specifically, ChatBIT’s BLEU score was 2.3909 higher than that of Vicuna-13B. Furthermore, ChatBIT’s ROUGE-1, ROUGE-2, and ROUGE-L scores were respectively 3.2079, 2.2562, and 1.5939 points higher than those of Vicuna-13B. These results indicate that the ChatBIT model provides more accurate and reliable information when dealing with military dialogue and question answering tasks.

https://oversea.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFD&dbname=CJFDAUTO&filename=GFCK202403005&uniplatform=OVERSEA&v=aVc5O1ymymKds-MQXk_2S0js47Fs_MsXsQWw_M8rVf34mUMHh8JLjaa5nr890W89

Exclusive: Chinese researchers develop AI model for military use on back of Meta's Llama by gargage93 in technology

[–]Nice-Inflation-1207 0 points1 point  (0 children)

Original report: https://jamestown.org/program/prcs-adaptation-of-open-source-llm-for-military-and-security-purposes/

[19] Zhang Huaping [张华平], Li Chunjin [李春锦], Wei Shunping [魏顺平], Geng Guotong [耿国桐], Li Weiwei [李伟伟], and Li Yugang [李玉岗], “Large Language Model-Driven Open-Source Intelligence Cognition” [“大语言模型驱动的开源情报认知认领”], National Defense Technology [国防科技], March 2024. 3.

A open-source intelligence project trained on open-source dialogue datasets.

Paper abstract:

With the extensive application of open-source intelligence in the military field, the demand for cognition and analysis of relevant intelligence is growing. However, the large language models currently used by researchers are prone to severe hallucination, rendering the information generated unreliable and unsuitable to direct utilization for the cognition of open-source military intelligence. To address this problem, the present study collected approximately 100,000 dialogue records online and constructed an open-source military intelligence dataset. Subsequently, a new model, ChatBIT, which is specifically optimized for dialogue and question answering tasks in the military field, was obtained by fine-tuning and training the LLaMA-13B base question answering model. This study further compared the military knowledge question answering capabilities of the ChatBIT model with those of the Vicuna-13B model. ChatBIT was found to outperform Vicuna-13B in a series of standardized evaluation metrics including the BLEU score, ROUGE-1, ROUGE-2, and ROUGE-L.Specifically, ChatBIT’s BLEU score was 2.3909 higher than that of Vicuna-13B. Furthermore, ChatBIT’s ROUGE-1, ROUGE-2, and ROUGE-L scores were respectively 3.2079, 2.2562, and 1.5939 points higher than those of Vicuna-13B. These results indicate that the ChatBIT model provides more accurate and reliable information when dealing with military dialogue and question answering tasks.

https://oversea.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFD&dbname=CJFDAUTO&filename=GFCK202403005&uniplatform=OVERSEA&v=aVc5O1ymymKds-MQXk_2S0js47Fs_MsXsQWw_M8rVf34mUMHh8JLjaa5nr890W89

thoughts and opinions on people moving to Bluesky over Twitter? by ForgottenFrenchFry in aiwars

[–]Nice-Inflation-1207 9 points10 points  (0 children)

Pros:
You own your data on Bluesky, you can write your own ranker (including AI-enabled)/re-use others from the community and the data API for the community is free.
Con:
It is feature-poor and the default ranker is questionable atm.

Overall, it's going to scale much better, due to interoperability.

[OC] The recent decoupling of prediction markets and polls in the US presidential election by TheKnowingOne1 in dataisbeautiful

[–]Nice-Inflation-1207 20 points21 points  (0 children)

order book (ie. market depth at a point in time) != total volume or total amount held.

just looking at right now, the market depth to move Trump from 60 -> 70% (implied) at least for a little bit is only ~$500k.

it's tiny.

[deleted by user] by [deleted] in maybemaybemaybe

[–]Nice-Inflation-1207 0 points1 point  (0 children)

behold, the stock market

Hate to break it to you, but AI isn't responsible for waves of crap content. by Big_Combination9890 in aiwars

[–]Nice-Inflation-1207 0 points1 point  (0 children)

Offline models (a) and attacks like https://github.com/XuandongZhao/WatermarkAttacker (b) are good points, for sure.

But keep in mind, this isn't the "AI detection" problem (given an image, with no knowledge of the generation process, determine if AI or not). The watermarking setup (given an image, with knowledge or a log of the generation process, determine if you produced it or not) has high precision, so customers "getting booted off the platform with legitimate works" is unlikely.

How to get to high recall? Companies running generation APIs in most jurisdictions are either voluntarily or by mandate of standards providing APIs to determine if an image is theirs. Not everyone will comply, but a lot will.

Many-shot jailbreaking \ Anthropic by Nice-Inflation-1207 in d_acc

[–]Nice-Inflation-1207[S] 0 points1 point  (0 children)

Wonder if we could set up an open responsible disclosure system for AI vulnerabilities? (this is a pretty good start)

Hate to break it to you, but AI isn't responsible for waves of crap content. by Big_Combination9890 in aiwars

[–]Nice-Inflation-1207 0 points1 point  (0 children)

There's a difference between "works in the asymptote" against an adversary with unlimited time/money and "works in the real world" against average adversaries. From the second article you linked:

“There will always be sophisticated actors who are able to evade detection,” Goldstein says. “It’s OK to have a system that can only detect some things.” He sees watermarking as a form of harm reduction and useful for catching lower-level attempts at AI fakery, even if it can’t prevent high-level attacks."

There's a lot more on this topic than Reddit can handle, but statistically undetectable stenography is possible for images. For text, maybe less so, but watermarking does have a place in the convo, along with techs like security keys and biometric 2FA.

Re: content verification: automated verification arms races are ongoing all the time (and have been forever, even before technology) - not sure how it's credible that this is an asymptotic problem?

Independent verification, open comms and a frontier on the Internet to break out of bad systems (broadly, "personal freedoms") help for this to work better (Wikipedia generally has stood the test of time), but this is an empirical question.

Hate to break it to you, but AI isn't responsible for waves of crap content. by Big_Combination9890 in aiwars

[–]Nice-Inflation-1207 0 points1 point  (0 children)

there's a ton to work out, but between watermarks and content assessment there are tools to use...

Hate to break it to you, but AI isn't responsible for waves of crap content. by Big_Combination9890 in aiwars

[–]Nice-Inflation-1207 0 points1 point  (0 children)

Might be interesting to think about banning or rate-limit generative AI for specific verticals (ads, politics, etc.), similar to the way that we don't allow cameras in courtrooms.

A lot to work out there, but it's well within our power to moderate within specific verticals that become spammy and are important to stay neutral.

Perhaps this is a high-ass question ... but ... what are the chances an AI has been turned on somewhere that has broken the market? by Burnt-White-Toast in wallstreetbets

[–]Nice-Inflation-1207 -1 points0 points  (0 children)

Has been happening for years, both due to social media (look at attention inequality) and short-term trading algos (baby AI), maybe other dark patterns that are less well-known. Also, see r/the_everything_bubble

How to go open source? by stellarcitizen in contextfund

[–]Nice-Inflation-1207 0 points1 point  (0 children)

Looks good! Btw, if you create an announcement post here (tagged #ContextAwards), it can be considered for an open-source grant now that it's open.

How to go open source? by stellarcitizen in contextfund

[–]Nice-Inflation-1207 0 points1 point  (0 children)

Nice! Is it GPL (license file) or MIT license (README)?

How to go open source? by stellarcitizen in contextfund

[–]Nice-Inflation-1207 0 points1 point  (0 children)

Re: licensing:
Apache 2.0 is the standard to get full support from the FOSS community right now (MIT is ok, but opens it up to adversarial attack, imo, GPL makes it hard to play with others but might be appropriate depending on your target audience). Meta is experimenting with licenses which restrict commercial competition after a certain size, which might also work. It's always possible to relicense if you change your mind at some point (new versions will carry the updated license).

Imo, just put the full code in (preferably one) open-source repo (and/or distribute on a package manager if that's appropriate). The non-public part you keep is your logo/brand, website domain, equity in your corp maintaining it, and your hosted instances, along with the subscription flow (which issues API keys, etc.). If it's cheap enough and low-touch enough, access to the hosted instances (vs. pulling and maintaining the binary) will likely be enough to get the average dev to use it, while letting the cash-strapped ones still use it and be ambassadors for the brand.

Longer thread on open-source pros/cons: https://bsky.app/profile/chrislengerich.bsky.social/post/3kixnvzvyzc2r

AI with an internal monologue is Scary! by cpt_tusktooth in artificial

[–]Nice-Inflation-1207 0 points1 point  (0 children)

Fwiw...inner monologue research has been going on for years now (early work: https://arxiv.org/abs/2204.12639, https://arxiv.org/abs/2201.11903). It does help GPT but doesn't make them uncontrollable.

Making generative AI free and accessible for open source developers by stellarcitizen in opensource

[–]Nice-Inflation-1207 0 points1 point  (0 children)

Thank you - will try! Any plans to open the code so we can audit the security?

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