• Quick note - the problem with Youtube videos not embedding on the forum appears to have been fixed, thanks to ZiprHead. If you do still see problems let me know.

Merged Artificial Intelligence

Puppycow

Penultimate Amazing
Joined
Jan 9, 2003
Messages
31,979
Location
Yokohama, Japan
I think we need a general thread on the topic. There are some others but they are narrower in scope.

Google claims new Gemini AI 'thinks more carefully'

Google has released an artificial intelligence (AI) model which it claims has advanced "reasoning capabilities" to "think more carefully" when answering hard questions.
Gemini was tested on its problem-solving and knowledge in 57 subject areas including maths and humanities.
Google is making some big claims for its new model, describing it as its "most capable" yet and has suggested it can outperform human experts in a range of intelligence tests.

Gemini can both recognise and generate text, images and audio - but is not a product in its own right.

Instead it is what it known as a foundational model, meaning it will be integrated into Google's existing tools, including search and Bard.
[Google] claims the most powerful version of Gemini outperforms OpenAI's platform GPT-4 - which drives ChatGPT - on 30 of the 32 widely-used academic benchmarks.

However, a new, more powerful version of the OpenAI software is due to be released next year, with chief executive Sam Altman saying the firm's new products would make its current ones look like "a quaint relative".

So, a number of interesting claims here.
1) The new AI can "outperform human experts in a range of intelligence tests"
2) It can also outperform GPT-4 on 30 out of 32 academic benchmarks
3) It can recognise and generate text, images and audio: not merely a chatbot

Is this, finally "AGI"? (I'm not asking if it's sentient, that's a separate question)

What is AGI (artificial general intelligence)?

An artificial general intelligence (AGI) is a hypothetical type of intelligent agent.[1] If realized, an AGI could learn to accomplish any intellectual task that human beings or animals can perform.[2][3] Alternatively, AGI has been defined as an autonomous system that surpasses human capabilities in the majority of economically valuable tasks.[4][promotion?] Creating AGI is a primary goal of some artificial intelligence research and of companies such as OpenAI,[4] DeepMind, and Anthropic. AGI is a common topic in science fiction and futures studies.

I'll say that it still needs to be demonstrated that it can meet either of those definitions. But even if it could "surpass human capabilities" in just a subset of economically valuable tasks, it would be quite interesting.
 
Last edited:
What I am interested in is how this A.I. is reaching its conclusions - is it just parsing the input more carefully and checks more references before copy&pasting something someone else already wrote?

Or can it really do advanced versions of "If A=B and B=C then..." and not just by brute force?
 
I'm noticing some new types of challenges for ReCaptcha and the like, perhaps to better combat AI solving the puzzles.
 
I think we need a general thread on the topic. There are some others but they are narrower in scope.

Google claims new Gemini AI 'thinks more carefully'



So, a number of interesting claims here.
1) The new AI can "outperform human experts in a range of intelligence tests"
2) It can also outperform GPT-4 on 30 out of 32 academic benchmarks
3) It can recognise and generate text, images and audio: not merely a chatbot

Is this, finally "AGI"? (I'm not asking if it's sentient, that's a separate question)

What is AGI (artificial general intelligence)?



I'll say that it still needs to be demonstrated that it can meet either of those definitions. But even if it could "surpass human capabilities" in just a subset of economically valuable tasks, it would be quite interesting.

No, this isn't AGI, though while some would disagree, I do think it's another step toward it. Will we eventually get to AGI with just larger models, bigger LLMs? I'm not really sure, but I'll give a definite maybe.

On the topic of performing better than GPT4 on 30 of 32 metrics, it seems it only performed marginally better, and there's some reason to suspect that it was tailored to those specific tasks.

So, in all, it seems like this is another step forward, but not a huge one.
 
I'm fascinated to see that lawsuits are springing up where AI group 1 accuses AI group 2 of using AI 1 to train AI2 (i.e. copying their work) ...

So... It's OK for you to rip off everything on the internet, but not OK when someone else does it to you?

Hypocrisy much?
 
I'm fascinated to see that lawsuits are springing up where AI group 1 accuses AI group 2 of using AI 1 to train AI2 (i.e. copying their work) ...

So... It's OK for you to rip off everything on the internet, but not OK when someone else does it to you?

Hypocrisy much?

Link please? I don't doubt it, but I don't know what you are referring to. What are the actual names of these "AI groups"?
 
I'm noticing some new types of challenges for ReCaptcha and the like, perhaps to better combat AI solving the puzzles.

I've read bots are now better at passing Captcha than humans. At this point it's just a worthless annoyance for people.
 
A new paper published in Nature this month, entitled Discovery of a structural class of antibiotics with explainable deep learning, in which a deep learning model was used to discover a new class of antibiotics.

https://www.nature.com/articles/s41586-023-06887-8
The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis1,2,3,4,5,6,7,8,9. Deep learning approaches have aided in exploring chemical spaces1,10,11,12,13,14,15; these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of 39,312 compounds and applied ensembles of graph neural networks to predict antibiotic activity and cytotoxicity for 12,076,365 compounds. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.
 

Back
Top Bottom