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Open Source AI is the collective inheritance of humanity IMO
"All stop All stop All stop" prevents any collision on the ground,
Introducing Devin, the groundbreaking AI software engineer that's revolutionizing the field of coding and problem-solving. Devin is the new state-of-the-art on the SWE-Bench coding benchmark, showcasing its unparalleled ability to tackle real-world engineering challenges.What sets Devin apart? This cutting-edge AI has successfully passed practical engineering interviews from top AI companies and has even completed real jobs on Upwork. Devin is a fully autonomous agent, equipped with its own shell, code editor, and web browser, enabling it to solve complex engineering tasks without human assistance.But the true test of Devin's capabilities lies in the SWE-Bench benchmark, which evaluates an AI's ability to resolve GitHub issues found in real-world open-source projects. Devin's performance is nothing short of remarkable, correctly resolving an astonishing 13.86% of the issues unassisted. This far exceeds the previous state-of-the-art model performance of 1.96% unassisted and 4.80% assisted, setting a new standard in the field of AI software engineering.!
Covariant, a robotics company, is pioneering the use of AI similar to ChatGPT to create robots that learn and operate in the real world, revolutionizing industries like warehousing. Their advanced technology allows robots to understand and interact with their environment in ways previously unimaginable, handling tasks with human-like understanding. By blending digital data with sensory inputs, Covariant's robots represent a significant leap forward in making intelligent, adaptable machines that can perform complex tasks alongside humans.
TLDRWe created a computer worm that targets GenAI-powered applications and demonstrated it against GenAI-powered email assistants in two use cases (spamming and exfiltrating personal data), under two settings (black-box and white-box accesses), using two types of input data (text and images) and against three different GenAI models (Gemini Pro, ChatGPT 4.0, and LLaVA).AbstractIn the past year, numerous companies have incorporated Generative AI (GenAI) capabilities into new and existing applications, forming interconnected Generative AI (GenAI) ecosystems consisting of semi/fully autonomous agents powered by GenAI services. While ongoing research highlighted risks associated with the GenAI layer of agents (e.g., dialog poisoning, privacy leakage, jailbreaking), a critical question emerges: Can attackers develop malware to exploit the GenAI component of an agent and launch cyber-attacks on the entire GenAI ecosystem?This paper introduces Morris II, the first worm designed to target GenAI ecosystems through the use of adversarial self-replicating prompts. The study demonstrates that attackers can insert such prompts into inputs that, when processed by GenAI models, prompt the model to replicate the input as output (replication) and engage in malicious activities (payload). Additionally, these inputs compel the agent to deliver them (propagate) to new agents by exploiting the connectivity within the GenAI ecosystem. We demonstrate the application of Morris II against GenAI-powered email assistants in two use cases (spamming and exfiltrating personal data), under two settings (black-box and white-box accesses), using two types of input data (text and images). The worm is tested against three different GenAI models (Gemini Pro, ChatGPT 4.0, and LLaVA), and various factors (e.g., propagation rate, replication, malicious activity) influencing the performance of the worm are evaluated.
Unfortunately it doesn't work for airplane already flying.
Quote from: hamdani yusuf on 13/03/2024 04:21:28Unfortunately it doesn't work for airplane already flying.As I mentioned in the next paragraph, airborne collisions are prevented by separation.
Devin, SIMA, Figure 01, all in 24 hours. What does it mean and are AI models taking the wheel? I?ll go through 5 relevant papers and 11 articles to get you all the relevant details, from what exactly Devin accomplished, and didn?t, to DeepMind's new AGI-attempt-in-3D (SIMA) to just how far AI agents have come and what that means for the future of jobs.
As the machines become more conscious, they will need their own version of moral standard they can follow and apply.
Figure 01 gave another incredible update on their progress. Their robot can now have entire conversations powered by ChatGPT. Plus, we look at other incredible robots making great progress.
What is AGI? What does it take to achieve AGI? What are the levels of AGI? 21:58 Leaked Document
Watch Nvidia CEO Jensen Huang show how Nvidia's Omniverse Cloud streams to Apple's Vision Pro XR headset.
Nvidia CEO Jensen Huang shows new robot technology at its GTC conference in San Jose.
See NVIDIA?s journey from pioneering advanced autonomous vehicle hardware and simulation tools to accelerated perception and manipulation for autonomous mobile robots and industrial arms, culminating in the next wave of cutting-edge AI for humanoid robots. Experience our journey from simulation to real-world deployment, showcasing our commitment to innovation and technological excellence.
Nvidia CEO Jensen Huang kicks off its GTC keynote in San Jose with a slew of AI infused chip announcements. Check out our recap right here.
Chapters:0:00 - Intro0:24 - 1X EVE3:02 - Project GROOT10:17 - Boston Dynamics13:07 - Mercedes Robot14:17 - Xiomai Dog Robot14:50 - Yondu Robot16:27 - Anduril Warfair Robot
It sounds like Q* is an upgrade from the greedy approach of LLMs where they only finding the highest probability of the next token in the answer, to finding the the highest probability of all the tokens put together. With my limited understanding in this, it sounds like they're accomplishing this with having a second latent space. So we basically go from a normal LLM: input-text -> latent space -> output-text, to Q*: input-text -> input latent space 1 -> latent space 2 (i.e. EBM) -> output latent space 1 -> output text.We might finally get an LLM that can answer the age-old question of "How many tokens are there in your response"
When AI can understand all humans
Probably an extreme case, but whenever I've worked in the field of disability and rehabilitation we have been faced with the infinite variability of human ability, multiplied by the infinite variability of human response to any interaction. Whatever you make or do for one patient, there is always somebody for whom it's not quite right and/or who wants it in a different color. To a lesser extent, teaching is the same.