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A computer scientist explains why even AI has computational limits

There are two aspects to a computer’s power: the number of operations its hardware can execute per second and the efficiency of the algorithms it runs. The hardware speed is limited by the laws of physics. Algorithms—basically sets of instructions —are written by humans and translated into a sequence of operations that computer hardware can execute. Even if a computer’s speed could reach the physical limit, computational hurdles remain due to the limits of algorithms.

These hurdles include problems that are impossible for computers to solve and problems that are theoretically solvable but in practice are beyond the capabilities of even the most powerful versions of today’s computers imaginable. Mathematicians and computer scientists attempt to determine whether a problem is solvable by trying them out on an imaginary machine.

Mercedes Claims to Have Achieved Level 3 Automation, Beating Tesla

German automaker Mercedes-Benz claims to have achieved Level 3 autonomy — “conditionally automated” vehicles that can monitor their driving environment and make informed decisions on behalf of the driver, but still require humans to occasionally take over — in the United States, an incremental but noteworthy step towards a future void of steering wheels and foot pedals.

“It is a very proud moment for everyone to continue this leadership and celebrate this monumental achievement as the first automotive company to be certified for Level 3 conditionally automated driving in the US market,” said Mercedes-Benz USA CEO Dimitris Psillakis in a statement.

The Rise of Automated Robots in the Future of Car Maintenance and Driving

The automobile business is continuously evolving, and as technology advances, we are seeing a shift toward a future of automated robots in the car maintenance sector. This move is expected to have a number of advantages, including greater accuracy and efficiency in automotive maintenance, as well as the capacity to work on older vehicles that traditional mechanics may be unfamiliar with.

As the owner of an older family truck, I have direct knowledge of the difficulty in finding a mechanic willing to work on their vehicle even if it is well kept up. With the emergence of automated robots, there will be no need to rely on human mechanics, as robots will be capable of doing the required jobs with ease. They will be able to detect faults and undertake routine maintenance, such as replacing belts, radiators, and other parts, without specialist training or knowledge.

The benefits of automated robots in automotive repair go beyond increased productivity. The robots will be built to work on a wide range of automobiles, regardless of age, allowing owners of older vehicles to maintain their vehicles without having to worry about finding a mechanic ready to work on them. Furthermore, automated robots will improve automotive maintenance accuracy since they will be equipped with cutting-edge technology and will be able to complete duties with precision and speed.

AI Replicated Evolution and Generated New Enzymes as Good as Natural Ones

Of those 100 proteins, the team created five of the artificial proteins and tested their functionality in cells, seeing how well they compared to an enzyme found in chicken eggs aptly named “hen egg white lysozyme” (HEWL). Two of the proteins demonstrated activity similar to HEWL, breaking down bacteria’s cell walls.

“The enzymes work (out-of-the-box) as well as proteins that have evolved over millions of years of evolution,” Madani said. The team also found that the model was able to capture evolutionary patterns, without specifically being trained to do so.

While AI has been used to generate proteins, this study differs a bit from prior research and further expands the idea of what is possible with language models.

Evolving Neural Networks Workshop

(see below for links to each of the sections)

The goal of the Evolving Neural Networks workshop is to bring together experts from Systems and Computational Neuroscience, Machine Learning and the Evo-Devo field to discuss if and how knowing the evolutionary history of neural circuits can help us understand the way the brain works, as well as the relative importance of learned VS innate neural mechanisms.

Sections:
00:00 — Intro.
4:30 — Intro 1st block.
11:35 — Pamela Lyon.
33:40 — Luis Puelles.
1:01:30 — Paul Cisek.
1:28:55 — Robert Yang.
1:58:40 — Discussion 1st block.
2:29:10-Intro 2nd block.
2:36:10 — Linda Wilbrecht.
3:02:45 — Ida Momennejad.
3:34:40 — Dayu Lin.
3:57:05 — Anthony Zador.
4:21:55 — Discussion 2nd block.
4:51:15 — Closing remarks.

Website: https://sites.google.com/view/evolving-nns/home

The Future of Robotics and Automation in Agriculture | TVS

Explore the cutting-edge technologies revolutionizing the world of agriculture. From self-driving tractors to robotic fruit pickers, learn how robotics and automation are improving crop yields, reducing labor costs, and making farming more sustainable. Discover the future of these technologies and how they are shaping the future of food production. This video is a must-watch for anyone interested in the intersection of technology and agriculture.

What are your thoughts on the future of robotics and automation in agriculture? Let us know!
Any disruptive technologies you would like us to cover? Dm us on our Instagram (@toyvirtualstructures).
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Bassbin Twins — A-1 Love

Will Google’s AI replace musicians?

No it can’t make music like Bassbin Twin because the music wasn’t programmed into the datasets from Google’s “Human experts” that limit what it can produce:

Read the fine print.

“We introduce MusicLM, a model generating high-fidelity music from text descriptions such as “a calming violin melody backed by a distorted guitar riff”. MusicLM casts the process of conditional music generation as a hierarchical sequence-to-sequence modeling task, and it generates music at 24 kHz that remains consistent over several minutes.


Classic track from The Edge, Ft. Lauderdale.

Ai Tells & Shows How it Will Wipe us Out

See AI describe in text and dozens of pictures the many ways it could wipe us out. See the power of Open AI’s ChatGPT and Stable Platform text to chat and text to art. Does this resemble some of the things already afoot by human characters today? What can we do about it?

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ChatGPT Is Coming for Classrooms. Don’t Panic

A double-whammy for systematic education since the need for knowledge-workers will decrease at the same time as AI fundamentally questions the need for / uses of “Knowledge Gatekeepers” — establishment academia, lawyers, even actors — the chatterbot classes.


When high school English teacher Kelly Gibson first encountered ChatGPT in December, the existential anxiety kicked in fast. While the internet delighted in the chatbot’s superficially sophisticated answers to users’ prompts, many educators were less amused. If anyone could ask ChatGPT to “write 300 words on what the green light symbolizes in The Great Gatsby,” what would stop students from feeding their homework to the bot? Speculation swirled about a new era of rampant cheating and even a death knell for essays, or education itself. “I thought, ‘Oh my god, this is literally what I teach,’” Gibson says.

But amid the panic, some enterprising teachers see ChatGPT as an opportunity to redesign what learning looks like—and what they invent could shape the future of the classroom. Gibson is one of them. After her initial alarm subsided, she spent her winter vacation tinkering with ChatGPT and figuring out ways to incorporate it into her lessons. She might ask kids to generate text using the bot and then edit it themselves to find the chatbot’s errors or improve upon its writing style. Gibson, who has been teaching for 25 years, likened it to more familiar tech tools that enhance, not replace, learning and critical thinking. “I don’t know how to do it well yet, but I want AI chatbots to become like calculators for writing,” she says.

Gibson’s view of ChatGPT as a teaching tool, not the perfect cheat, brings up a crucial point: ChatGPT is not intelligent in the way people are, despite its ability to spew humanlike text. It is a statistical machine that can sometimes regurgitate or create falsehoods and often needs guidance and further edits to get things right.

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