This request for information does cover some of the possible existential risks, in the first section. I am going to submit a few responses of my own, and I am hopeful others will do the same. 1. What specific measures – such as standards, regulations, investments, and improved trust and...
A recent discovery of large language models like GPT-3 and Instruct-GPT have shown that specific prompts can elicit text generation that follows some basic reasoning. These chain of thought prompts can be as simple as "Let's think step by step" and create zero shot successes on math word problems and...
Thank you for writing this up. I agree with just about everything said.
The majority of my response is in reducing our systems exposure vulnerabilities. As a believer in the power of strong cryptography no matter the intelligence involved, I am going to explain the value of removing or spinning down of the NSA/CIA program of back-doors, zero day exploits, and intentional cryptographic weaknesses that have been introduced into our hardware and software infrastructure.
This request for information does cover some of the possible existential risks, in the first section. I am going to submit a few responses of my own, and I am hopeful others will do the same.
1. What specific measures – such as standards, regulations, investments, and improved trust and safety practices – are needed to ensure that AI systems are designed, developed, and deployed in a manner that protects people’s rights and safety? Which specific entities should develop and implement these measures?
2. How can the principles and practices for identifying and mitigating risks from AI, as outlined in the Blueprint for an AI Bill of Rights and the AI Risk Management... (read 158 more words →)
Do you still hold this belief?
Language is one defining aspect of intelligence in general and human intelligence in particular. That an AGI wouldn't utilize the capability of LLM's doesn't seem credible. The cross modal use cases for visual perception improvements (self-supervised labeling, pixel level segmentation, scene interpretation, casual inference) can be seen in recent ICLR/CVPR papers. The creation of github.com/google/BIG-bench should lend some credence that many leading institutions see a path forward with LLM's.
If current trends hold, then large language models will be a pillar in creating AGI; which seems uncontroversial. I think one can then argue that after ignoring the circus around sentience means we should focus on the new current capabilities: reasoning, and intricate knowledge of how humans think and communicate. From that perspective there is a now a much stronger argument for manipulation. Outwitting humans prior to having human level intelligence is a major coup. PaLM's ability to explain a joke and reason it's way to understanding the collective human psyche is as impressive to me as Alphafold.
The goal posts have been moved on the Turing test and it's important to point that out in any debate. Those in the liberal A.I. bias community have to at least acknowledge the particular danger of these LLM models that can reason positions. Naysayers need to have it thrown in their face that these lesser non-sentient, neural networks trained on a collection of words will eventually out debate them.
It is bizarre watching people like him and Gary Marcus embarrass themselves. It's like watching Boomers saying they'll never see another shooter as good as Larry Bird, all while Steph Curry is blasting through every NBA record of note.
As autonomous agents become more widespread, the risk becomes more obvious. Dyson and Tesla will be pumping out androids in 8 years. Starlink will provide the bandwidth to control any internet connected IoT device. Security Zero day back doors are discovered every month, that don't even include the intentional nation state added ones. I personally thought the wake-up call would happen with the deployment of Ghost Drones (not fully autonomous but easily could be). Max Tegmark's #banslaughterbots campaign is going nowhere as drones will continue to show combat effectiveness. At this point, the proverbial water is going to be near boiling and many people will still say "Sauna doesn't have enough jets."
Is anyone at MIRI or Anthropic creating diagnostic tools for monitoring neural networks? Something that could analyze for when a system has bit-flip errors versus errors of logic, and eventually evidence of deception.
It's unfortunate we couldn't have a Sword of Damocles deadman switch in case of AGI led demise. A world ending asteroid positioned to go off in case of "all humans falling over dead at the same time." At least that would spare the Milky Way and Andromeda possible future civilizations. A radio beacon warning about building intelligent systems would be beneficial as well. "Don't be this stupid" written in the glowing embers of our solar system.
A recent discovery of large language models like GPT-3 and Instruct-GPT have shown that specific prompts can elicit text generation that follows some basic reasoning. These chain of thought prompts can be as simple as "Let's think step by step" and create zero shot successes on math word problems and critical thinking. Although these LLM models are not AGI, they are built with the now ubiquitous Transformer architecture that future multi-model proto AGI might be based upon. Hopefully, future models will answer important ethical questions and could at least give an indication of the thought processes behind the outputs.
In the the paper, (https://arxiv.org/pdf/2205.11916v1.pdf) some examples of the failures of the model... (read 919 more words →)
OpenAI delivering an iterative update rather than a revolutionary one has lengthened many people's timelines. My take is that this incentivizes many more players into trying for the frontier. Xai's Grok has gone from non-existent in 2022 to a leading model. The rollout pace of improvements to the newest version of Grok are far more frequent than other leading companies. Nvidia has also recently begun releasing open larger source models as well as the accompanyin datasets. Meta is another player that is now all-in. The failure of Llama and moderate updates by OpenAI likely pushed Zuckerberg into realizing that his favored relentless A/B testing at scale could work. Twenty-nine billion for new... (read more)