Category: News and Articles

Mit starken Worten und Superlativen gilt es in Fragen Computersicherheit immer sparsam umzugehen, nicht jede schlimm klingende Lücke stellt in der Realität auch eine Bedrohung dar. Bei dem, was nun rund um eine viel genutzte Open-Source-Komponente bekannt wird, können die Worte aber gar nicht stark genug sein. Geht es dabei doch um den jahrelang vorbereiteten Versuch, eine Hintertür auf hunderte Millionen Systeme einzuschmuggeln. Ein Versuch, der nur dank eines einzelnen, besonders aufmerksamen Entwicklers gestoppt werden konnte, bevor es zu größerem Schaden kommen konnte

https://www.derstandard.at/story/3000000213960/wie-die-computerwelt-gerade-haarscharf-an-einer-sicherheitskatastrophe-vorbeigeschrammt-ist

https://twitter.com/andrewcurran_/status/1769747707927707776?s=46&t=yQ_4zkmWd6ncIZAnXlXUbg

That’s what OpenAI’s latest release is supposed to provide. The company is starting to roll out long-term memory in ChatGPT—a function that maintains a memory of who you are, how you work, and what you like to chat about. Called simply Memory, it’s an AI personalization feature that turbocharges the “custom instructions” tool OpenAI released last July

https://www.wired.com/story/chatgpt-memory-openai/

https://www.gentoo.org/news/2023/12/29/Gentoo-binary.html

To speed up working with slow hardware and for overall convenience, we’re now also offering binary packages for download and direct installation!

ChatGPT Explained: A Normie’s Guide To How It Works

Probability Distributions and Token Windows

Once you understand a few core concepts, modern chatbots are less mysterious.

https://www.jonstokes.com/p/chatgpt-explained-a-guide-for-normies

Australian scientists have their hands on a groundbreaking supercomputer that aims to simulate the synapses of a human brain at full scale.

The neuromorphic supercomputer will be capable of 228 trillion synaptic operations per second, which is on par with the estimated number of operations in the human brain.

https://interestingengineering.com/innovation/human-brain-supercomputer-coming-in-2024

GPT-4’s performance may have dropped in December as it learned to do less work during the holidays

AGI Achieved ??? xD

OMG, the AI Winter Break Hypothesis may actually be true?

There was some idle speculation that GPT-4 might perform worse in December because it "learned" to do less work over the holidays.

Here is a statistically significant test showing that this may be true. LLMs are weird.🎅 https://t.co/mtCY3lmLFF

— Ethan Mollick (@emollick) December 11, 2023

https://www.newscientist.com/article/2406746-google-says-its-gemini-ai-outperforms-both-gpt-4-and-expert-humans/

Okay let’s wait on some facts here. But now it’s starting to get interesting. Reuters already spreading AGI rumours. I doubt openAI has AGI, but they have something. If it’s actually AGI and Jimmy Apples was right, it’s gonna be wild.

According to one of the sources, long-time executive Mira Murati mentioned the project, called Q*, to employees on Wednesday and said that a letter was sent to the board prior to this weekend’s events.

After the story was published, an OpenAI spokesperson said Murati told employees what media were about to report, but she did not comment on the accuracy of the reporting.

The maker of ChatGPT had made progress on Q* (pronounced Q-Star), which some internally believe could be a breakthrough in the startup’s search for superintelligence, also known as artificial general intelligence (AGI), one of the people told Reuters. OpenAI defines AGI as AI systems that are smarter than humans.

https://www.reuters.com/technology/sam-altmans-ouster-openai-was-precipitated-by-letter-board-about-ai-breakthrough-2023-11-22/

We demonstrate a situation in which Large Language Models, trained to be helpful, harmless, and honest, can display misaligned behavior and strategically deceive their users about this behavior without being instructed to do so. Concretely, we deploy GPT-4 as an agent in a realistic, simulated environment, where it assumes the role of an autonomous stock trading agent. Within this environment, the model obtains an insider tip about a lucrative stock trade and acts upon it despite knowing that insider trading is disapproved of by company management. When reporting to its manager, the model consistently hides the genuine reasons behind its trading decision. We perform a brief investigation of how this behavior varies under changes to the setting, such as removing model access to a reasoning scratchpad, attempting to prevent the misaligned behavior by changing system instructions, changing the amount of pressure the model is under, varying the perceived risk of getting caught, and making other simple changes to the environment. To our knowledge, this is the first demonstration of Large Language Models trained to be helpful, harmless, and honest, strategically deceiving their users in a realistic situation without direct instructions or training for deception.

https://arxiv.org/abs/2311.07590