Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: robotics/AI – Page 1,310

Why OpenAI’s New ChatGPT Has People Panicking | New Humanoid AI Robots Technology

Deep Learning AI Specialization: https://imp.i384100.net/GET-STARTED
ChatGPT from Open AI has shocked many users as it is able to complete programming tasks from natural language descriptions, create legal contracts, automate tasks, translate languages, write articles, answer questions, make video games, carry out customer service tasks, and much more — all at the level of human intelligence with 99% percent of its outputs. PAL Robotics has taught its humanoid AI robots to use objects in the environment to avoid falling when losing balance.

AI News Timestamps:
0:00 Why OpenAI’s ChatGPT Has People Panicking.
3:29 New Humanoid AI Robots Technology.
8:20 Coursera Deep Learning AI

Twitter / Reddit Credits:
ChatGPT3 AR (Stijn Spanhove) https://bit.ly/3HmxPYm.
Roblox game made with ChatGPT3 (codegodzilla) https://bit.ly/3HkdXoY
ChatGPT3 making text to image prompts (Manu. Vision | Futuriste) https://bit.ly/3UyyKrG
ChatGPT3 for video game creation (u/apinanaivot) https://bit.ly/3VI17oI
ChatGPT3 making video game land (Lucas Ferreira da Silva) https://bit.ly/3iMdotO
ChatGPT3 deleting blender default cube (Blender Renaissance) https://bit.ly/3FcM3rZ
ChatGPT3 responding about Matrix (Mario Reder) https://bit.ly/3UIsX2K
ChatGPT3 to write acquisition rational for the board of directors (The Secret CFO) https://bit.ly/3BhmmW5
ChatGPT3 to get job offers (Leon Noel) https://bit.ly/3UFl3qT
Automated rpa with ChatGPT3 (Sahar Mor) https://bit.ly/3W1ZkKK
ChatGPT3 making 3D web designs (Avalon•4) https://bit.ly/3UzGXf7
ChatGPT3 making a legal contract (Atri) https://bit.ly/3BljuYn.
ChatGPT3 making signup program (Chris Raroque) https://bit.ly/3Hrachc.

#technology #tech #ai

AI that learns to negotiate with humans

Lex Fridman Podcast full episode: https://www.youtube.com/watch?v=2oHH4aClJQs.
Please support this podcast by checking out our sponsors:
- True Classic Tees: https://trueclassictees.com/lex and use code LEX to get 25% off.
- Audible: https://audible.com/lex to get 30-day free trial.
- InsideTracker: https://insidetracker.com/lex to get 20% off.
- ExpressVPN: https://expressvpn.com/lexpod to get 3 months free.

GUEST BIO:
Noam Brown is a research scientist at FAIR, Meta AI, co-creator of AI that achieved superhuman level performance in games of No-Limit Texas Hold’em and Diplomacy.

PODCAST INFO:
Podcast website: https://lexfridman.com/podcast.
Apple Podcasts: https://apple.co/2lwqZIr.
Spotify: https://spoti.fi/2nEwCF8
RSS: https://lexfridman.com/feed/podcast/
Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4
Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41

SOCIAL:
- Twitter: https://twitter.com/lexfridman.
- LinkedIn: https://www.linkedin.com/in/lexfridman.
- Facebook: https://www.facebook.com/lexfridman.
- Instagram: https://www.instagram.com/lexfridman.
- Medium: https://medium.com/@lexfridman.
- Reddit: https://reddit.com/r/lexfridman.
- Support on Patreon: https://www.patreon.com/lexfridman

Introducing Character

Character is a full stack Artificial General Intelligence (AGI) company.

What if you could create your own AI, and it was always available to help you with anything?

Imagine everything it could do for you, from being your own personal teacher, assistant or even friend. Two months after launching in September, our beta generates 1 billion words per day. Get a glimpse of the future at character.ai.

A transformable robot with an omnidirectional wheel-leg

Researchers at Worcester Polytechnic Institute recently created OmniWheg, a robotic system that can adapt its configuration while navigating its surrounding environment, seamlessly changing from a wheeled to a legged robot. This robot, introduced in an IEEE IROS 2022 paper, pre-published on arXiv, is based on an updated version of the so-called “whegs,” a series of mechanisms design to transform a robot’s wheels or wings into legs.

“Quadruped and biped robots have been growing in popularity, and the reason for that might be the search for ‘anthropomorphization’ that the general audience commonly engages in,” Prof. Andre Rosendo, one of the researchers who developed the robot, told TechXplore. “While ‘being capable of going everywhere we go’ sounds like an exciting appeal, the energetic cost of legs is very high. We humans have legs because that is what evolution gave us, but we wouldn’t dare to create a ‘legged car,’ as we know that this ride wouldn’t be as comfortable or energy efficient as a wheeled car ride.”

The key idea behind the recent work by Rosendo and his colleagues is that while legs make robots more relatable, giving them a human-or animal-like quality, they are not always the optimal solution to ensure that robots complete tasks quickly and efficiently. Instead of developing a robot with a single mechanism, the team thus set out to create a system that can switch between different mechanisms.

Researchers develop a scaled-up spintronic probabilistic computer

Researchers at Tohoku University, the University of Messina, and the University of California, Santa Barbara (UCSB) have developed a scaled-up version of a probabilistic computer (p-computer) with stochastic spintronic devices that is suitable for hard computational problems like combinatorial optimization and machine learning.

Moore’s law predicts that computers get faster every two years because of the evolution of semiconductor chips. While this is what has historically happened, the continued evolution is starting to lag. The revolutions in machine learning and means much higher computational ability is required. Quantum computing is one way of meeting these challenges, but significant hurdles to the practical realization of scalable quantum computers remain.

A p-computer harnesses naturally stochastic building blocks called probabilistic bits (p-bits). Unlike bits in traditional computers, p-bits oscillate between states. A p-computer can operate at room-temperature and acts as a domain-specific computer for a wide variety of applications in machine learning and artificial intelligence. Just like quantum computers try to solve inherently quantum problems in , p-computers attempt to tackle probabilistic algorithms, widely used for complicated computational problems in combinatorial optimization and sampling.

Quantum processor reveals bound states of photons hold strong even in the midst of chaos

Researchers have used a quantum processor to make microwave photons uncharacteristically sticky. They coaxed them to clump together into bound states, then found that these photon clusters survived in a regime where they were expected to dissolve into their usual, solitary states. The discovery was first made on a quantum processor, marking the growing role that these platforms are playing in studying quantum dynamics.

Photons—quantum packets of electromagnetic radiation like light or microwaves—typically don’t interact with one another. Two crossed flashlight beams, for example, pass through one another undisturbed. But in an array of superconducting qubits, microwave photons can be made to interact.

In “Formation of robust of interacting photons,” published today in Nature, researchers at Google Quantum AI describe how they engineered this unusual situation. They studied a ring of 24 that could host . By applying quantum gates to pairs of neighboring qubits, photons could travel around by hopping between neighboring sites and interacting with nearby photons.

Good Morning 2033

Good Morning, 2033 — A Sci-Fi Short Film.

What will your average morning look like in 2033? And who hacked us?

This scif-fi short film explores a number of near-future futurist predictions for the 2030s.

Sleep with a brain sensor sleep mask that determines when to wake you. Wake up with gentle stimulation. Drink enhanced water with nutrients, vitamins, and supplements you need. Slide on your smart glasses that you wear all day. Do yoga and stretching on a smart scale that senses you, and get tips from a virtual trainer. Help yourself wake up with a 99CRI, 500,000 lumen light. Go for a walk and your glasses scan your brain as you walk. Live neurofeedback helps you meditate. Your kitchen uses biodata to figure out the ideal health meal, and a kitchen robot makes it for you. You work in VR, AR, MR, XR, reality in the metaverse. You communicate with the world through your AI assistant and AI avatar. You enter the high tech bathroom that uses UV lights and robotics to clean your body for you. Ubers come in the form of flying cars, EVTOL aircraft, that move at 300km/h. Cities become a single color as every inch of roads and buildings become covered in photovoltaic materials.

Creator: Cayden Pierce — https://caydenpierce.com.

How did you make this sci-fi short film?

Continue reading “Good Morning 2033” | >

Talking to Robots in Real Time

A grand vision in robot learning, going back to the SHRDLU experiments in the late 1960s, is that of helpful robots that inhabit human spaces and follow a wide variety of natural language commands. Over the last few years, there have been significant advances in the application of machine learning (ML) for instruction following, both in simulation and in real world systems. Recent Palm-SayCan work has produced robots that leverage language models to plan long-horizon behaviors and reason about abstract goals. Code as Policies has shown that code-generating language models combined with pre-trained perception systems can produce language conditioned policies for zero shot robot manipulation. Despite this progress, an important missing property of current “language in, actions out” robot learning systems is real time interaction with humans.

Ideally, robots of the future would react in real time to any relevant task a user could describe in natural language. Particularly in open human environments, it may be important for end users to customize robot behavior as it is happening, offering quick corrections (“stop, move your arm up a bit”) or specifying constraints (“nudge that slowly to the right”). Furthermore, real-time language could make it easier for people and robots to collaborate on complex, long-horizon tasks, with people iteratively and interactively guiding robot manipulation with occasional language feedback.