This robot carries your groceries wherever you go.
Grocery robot
Posted in robotics/AI
Category: robotics/AI – Page 1603
A robot that mimics the way squid move is most efficient when it operates with a particular rhythm.
Tesla recently shared some footage of its next-generation 4680 battery cells being produced. The video, which seems to be taken from the electric car maker’s pilot Roadrunner line, suggests that Tesla’s 4680 battery manufacturing system may very well be Elon Musk’s elusive “Alien Dreadnought” concept coming to life.
During the lead up to the Model 3’s initial ramp, Elon Musk envisioned a vehicle production system that was so automated, it would look extraterrestrial in nature. Dubbed as the “Alien Dreadnought,” this concept ultimately fell short of its targets, and Tesla eventually adopted a production system for the Model 3 that combined both human and automated machines. Since then, Tesla has taken steps towards increasing the automation of its vehicle production system, as evidenced by parts like the Model Y’s rigid wiring, which are optimized for installation by robots.
Tesla’s video of its 4680 battery production line suggests that the company’s level of automation has reached levels that have never been seen before. As noted by TSLA bull @truth_tesla on Twitter, the footage shared by Tesla in its recruitment video showed a battery production line that is incredibly automated. This could be seen immediately in Tesla’s main battery production line, which, unlike traditional battery manufacturing facilities, is largely absent of human workers.
New technology from Stanford scientists finds long-hidden quakes, and possible clues about how earthquakes evolve.
Tiny movements in Earth’s outermost layer may provide a Rosetta Stone for deciphering the physics and warning signs of big quakes. New algorithms that work a little like human vision are now detecting these long-hidden microquakes in the growing mountain of seismic data.
Measures of Earth’s vibrations zigged and zagged across Mostafa Mousavi’s screen one morning in Memphis, Tenn. As part of his PhD studies in geophysics, he sat scanning earthquake signals recorded the night before, verifying that decades-old algorithms had detected true earthquakes rather than tremors generated by ordinary things like crashing waves, passing trucks or stomping football fans.
AI to the Future
Posted in robotics/AI, singularity, transportation
From self-driving cars, to the many automated production processes we will end up creating; we will allow AI drive us into the next era of human civilization.
We will allow the creation to create, and according to futurist and technologists’ world over, there is only one likely path where this road will lead to — the Singularity (the point where computer intelligence surpasses human intelligence).
- The Above is an excerpt from the book, 2020s & The Future Beyond.
Will be happy to hear the thoughts of group members.
#Iconickelx.
I like this idea. I don’t want AI to be a black box, I want to know what’s happening and how its doing it.
The field of artificial intelligence has created computers that can drive cars, synthesize chemical compounds, fold proteins, and detect high-energy particles at a superhuman level.
However, these AI algorithms cannot explain the thought processes behind their decisions. A computer that masters protein folding and also tells researchers more about the rules of biology is much more useful than a computer that folds proteins without explanation.
Therefore, AI researchers like me are now turning our efforts toward developing AI algorithms that can explain themselves in a manner that humans can understand. If we can do this, I believe that AI will be able to uncover and teach people new facts about the world that have not yet been discovered, leading to new innovations.
Both AlphaFold’s and GPT-3’s success was due largely to the massive datasets they were trained on; no revolutionary new training methods or architectures were involved. If all it was going to take to advance AI was a continuation or scaling-up of this paradigm—more input data yields increased capability—China could well have an advantage.
But one of the biggest hurdles AI needs to clear to advance in leaps and bounds rather than baby steps is precisely this reliance on extensive, task-specific data. Other significant challenges include the technology’s fast approach to the limits of current computing power and its immense energy consumption.
Thus, while China’s trove of data may give it an advantage now, it may not be much of a long-term foothold on the climb to AI dominance. It’s useful for building products that incorporate or rely on today’s AI, but not for pushing the needle on how artificially intelligent systems learn. WeChat data on users’ spending habits, for example, would be valuable in building an AI that helps people save money or suggests items they might want to purchase. It will enable (and already has enabled) highly tailored products that will earn their creators and the companies that use them a lot of money.
Samsung’s memory technology innovates artificial intelligence and Big Data analytics to bring impactful change to the way we live, work, and interact with each other. Through next-generation memory technology that enables faster and more complex tasks in AI and Big Data, Samsung takes part in the revolutionary advancement of technology that is enriching our everyday lives.
Neural networks of neural networks.
Brains receive input from the outside world, their neurons do something to that input, and create an output. That output may be a thought (I want curry for dinner); it may be an action (make curry); it may be a change in mood (yay curry!). Whatever the output, that “something” is a transformation of some form of input (a menu) to output (“chicken dansak, please”). And if we think of a brain as a device that transforms inputs to outputs then, inexorably, the computer becomes our analogy of choice.
For some this analogy is merely a useful rhetorical device; for others it is a serious idea. But the brain isn’t a computer. Each neuron is a computer. Your cortex contains 17 billion computers.