#artificial intelligence chip

[rotting-brains]

they couldn't do a mcsm season 3 because if petra had to suffer for plot reasons for a single other episode she would die

[inkintheinternet]

Ai Philosophers Thinkers of the New World

By Arjuwan Lakkdawala

Ink in the Internet

After writing had been established in the world - its origin going back to Mesopotamia (ancient Iraq) closely followed by Ancient Egypt and China, the records show Greek philosophers with overwhelming efforts trying to articulate into words mysteries of the natural world, reason and logic, concepts of what makes a good life, and of course questions about ethics and existence. In my research I found 9 Greek philosophers, to mention a few of them Pythagoras (notoriously famous for the Pythagoras Theorem).

Side Note: "Although the theorem has long been associated with Greek mathematician-philosopher Pythagoras (c. 570–500/490 BCE), it is actually far older. Four Babylonian tablets from circa 1900–1600 BCE indicate some knowledge of the theorem, with a very accurate calculation of the square root of 2."

Protagoras, Socrates, Plato, and Aristotle. It is said that western thought is highly influenced by them. As history unfolded we know that many philosophers expressed their ideas, and presently we have an infinite maze of ideologies.

In a free world everyone believes what they want to believe, but if it is harmful to society, causes self harm, is illogical, then it should be illegal and wrong.

Up to now we were doing all the thinking, but presently there is an emerging new class of very different thinkers, and that is Artificial Intelligence, computer scientists are taking big data which is basically infinite and feeding it to Ai, and concepts from neuroscience is being used to develope more powerful computing like neuromorphic chips.

A study published in Neuron in 2022 explains "Bioneural Circuitry." In simple words, neurons use electricity to send signals so it is possible to merge them with electrical signals from artificial intelligence on electrodes. This could be similar to the technology used by Neuralink implants.

A very futuristic idea that occurred to me is what if a hypothetical Ai (Star-Sci) is used as a teacher from kindergarten to university graduation, with constant upgrade of information as the years go by. This teacher would teach and even give tests. An Ai model that teaches everything. Students would instead of naming universities or a string of teachers, be known only as pupils of a certain Ai. This is of course a very sci-fi idea, but in realistic terms as I see anarchy increasing in the world, and the cases of teachers behaving inappropriately with students, I think Ai teachers will be looked upon favourably pretty soon.

After thought: academics can contribute for free or paid to the Star-Sci life long teaching system. This could be a new style university, where students only interect with Ai, preventing any non-educational use of the institute or corruption from fellow students or teachers.

We in this current age are going through the greatest social experiment. That is the Internet which is a merging of human mind with artificial intelligence. It is changing the world in ways we cannot predict as this hasn't happened before. We have no previous case studies.

Ai is reportedly often used in writing essays, I personally use search engines for my research. I avoid using Ai to do any of my writing, I don't want my mind to rely on artificial intelligence, because I believe it will corrode my much superior human intelligence.

I think artificial intelligence is good to use in the management of big data, but not in any paper with concepts within the ability of human calculation and comprehension.

Scientists are trying to come up with a unified theory of consciousness. According to research and most human experiences we have an outer sense in which we comprehend empirical evidance and what we immediately experience, and then we have an inner consciousness in which we think, form memories and plan ahead. The outer world is not really complicated, it's the inner world - thoughts that can warp into unknown manesfeststions, some of these neurological paths can lead to genuise and others to insanity.

This unknown manesfestations of consciousness is exactly what defines the difference between human thinking and Ai programming. Artificial intelligence cannot have thoughts at all. It can only compute programmed instructions based on the data it has. But with big data this programming could in the near future start to resemble consciousness. As we do not and mentally cannot compute big data, so the output of Ai from big data could seem to us like independent thoughts.

It is crucial to understand this about Ai as technology integrates it further in our lives and we interact with it increasingly.

At the same time we must avoid using it where we can use our human intelligence. This is of prime importance if we are to preserve the excellence of our cognitive abilities.

Neuroscience studies reveal that neural networks that are not used get lost. We don't really need scientific experiments to confirm this, as we can immediately tell when our memory improves, or we get better at any intellectual skill, well known that it only happens with practice, therefore if we rely on Ai it will result gradually in mental decline.

As we think our brains form complex neural networks that improve our intelligence regarding a study or concept.

Thoughts are different than feelings, we have often heard that the brain is logical and sensible while the heart isn't. Studies have confirmed that the heart has a neural network known as the intrinsic cardiac nervous system (ICNS). While this does not say that it is why we have feelings that could contradict our intelligence, it is an interesting hypothetical concept to explain how feelings and logical thoughts can be in conflict with each other.

Being irrational and illogical or hateful, and having several other destructive traits, that cause self harm, or harm to society, is unfortunately observed more often these days.

Mental health is a very complicated and difficult terrain to traverse, we are nothing without our consciousness. Our whole quality of life depends on the level of our intelligence and the health of our minds - this is maintained and achieved by a good upbringing, secure environment, healthy diet, and a rounded education with physical exercise.

There are foods that improve the health of our brains, and foods that increase the risk of Alzheimer's disease and dementia and have other negatives effects. Google for articles about brain health foods.

(I have added notes to this articles in the comments section).

Arjuwan Lakkdawala is an author and independent science researcher.

X/Twitter/Instagram: Spellrainia

Email: arjuwan.writer@gmail.com

Copyright ©️ Arjuwan Lakkdawala 2024

Sources:

MBF Bioscience - Researchers map and explore the heart's "little brain"

Psychology Today - Neuroplasticity - reviewed by Psychology Today staff

Medium - Neuromorphic Computing

ABclonal Knowledge Base - Melding Neuroscience with Computer Technology  - Kin Leung

Pythagorean Theorem - written and fact checked by the editors of Britannica Encyclopedia

Singularity Hub - Scientists are Working Towards a Unified Theory of Consciousness  - Shelly Fan

The Collector - 9 Greek Philosophers who Shaped the World - Eddie Hodsdon, BA professional Writing, member Canterbury Archealogical Trust

[jcmarchi]

DeepSeek's AI breakthrough: Fewer resources, big impact

New Post has been published on https://thedigitalinsider.com/deepseeks-ai-breakthrough-fewer-resources-big-impact/

DeepSeek's AI breakthrough: Fewer resources, big impact

On December 26th, a modest-sized Chinese company named DeepSeek introduced advanced AI technology, rivaling the top chatbot systems from giants like OpenAI and Google.

This achievement was noteworthy for its capability and the cost-efficiency with which it was developed. Unlike its large competitors, DeepSeek created its artificial intelligence, DeepSeek-V3, using significantly fewer specialized processors, which are typically essential for such advancements.

Cost efficiency and technological breakthrough

These processors are at the heart of a fierce tech rivalry between the U.S. and China. The U.S. aims to keep its lead in AI by restricting the export of high-end chips, such as those from Nvidia, to China.

However, DeepSeek’s success with fewer resources raises concerns about the effectiveness of U.S. trade policies, which have inadvertently spurred Chinese innovation using more accessible technologies.

DeepSeek-V3 impressively handles tasks like answering queries, solving puzzles, programming, and matching industry standards. Remarkably, it was developed with just around $6 million worth of computing resources, starkly contrasting the $100 million Meta reportedly invested in similar technologies.

Chris V. Nicholson from Page One Ventures pointed out that more companies could afford $6 million than the heftier sums, democratizing access to advanced AI technology.

Strategic implications and global impact of DeepSeek

Previously, experts believed only firms with substantial financial resources could compete with leading AI firms, which train their systems on supercomputers requiring thousands of chips.

DeepSeek, however, managed with just 2,000 chips from Nvidia. This efficient use of limited resources reflects the forced innovation resulting from chip restrictions in China, as Jeffrey Ding from George Washington University noted.

Recently, the U.S. tightened these restrictions to prevent China from acquiring advanced AI chips via third countries. This is part of ongoing efforts to limit Chinese firms’ potential military use of these technologies, which have resorted to stockpiling chips and sourcing them through underground markets.

ChatGPT vs Bard: What are the top key differences?

We’re taking a look at Bard vs ChatGPT and their key differences like technology, internet connection, and training data.

DeepSeek, a company rooted in quantitative stock trading, has been leveraging its profits to invest in Nvidia chips since 2021, fueling its AI research rather than consumer products. This focus has allowed it to bypass stringent Chinese regulations on consumer AI, attracting top talent and exploring diverse applications from poetry to complex examinations.

While leading U.S. firms continue to push AI boundaries, DeepSeek’s recent achievements underline its growing prowess in the field. It also highlights the broader shift towards open-source AI, gaining traction as companies like Meta openly share their technologies. This shift increasingly positions China as a central player in AI development, posing a strategic challenge to U.S. dominance in the field.

As the debate continues over the potential risks of open sourcing AI in the U.S., such as spreading misinformation, the global open source community, increasingly led by China, might shape the future of AI development, suggesting a significant geopolitical shift in the technology landscape.

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[peterbordes]

Nvidia’s Jensen Huang says AI agents are ‘a multi-trillion-dollar opportunity’ at last nights CES AI keynote. Let that “multi Trillion” sink in, because this global movement is just getting started.

[memenewsdotcom]

Nvidia stock rises by record

[fastlivenostress]

Elon Musk's Ambitious Plan to Implant Brain Chips: What You Need to Know

Elon Musk, the visionary entrepreneur and founder of SpaceX, Tesla, and The Boring Company, has set his sights on an incredibly ambitious project: implanting brain chips into humans. This may sound like science fiction, but Musk’s Neuralink company has already made significant progress in developing a brain-computer interface that could revolutionize the way we interact with technology. In this…

[khayal12345]

First photovoltaic leaf in history created ― Infinite energy with “living chips”

[aitalksblog]

Top Weekly AI News – February 07, 2025

AI News Roundup – February 07, 2025 Global chip sales rose 19.1% in 2024 and will hit double digit growth in 2025 thanks to AI | SIA The SIA reports record-breaking global chip sales in 2024, driven by strong demand for AI processors and memory venturebeat Feb 07, 2025 Researchers trained an OpenAI rival in half an hour for less than $50 Researchers developed a low-cost AI model, s1,…

[northsentinelmapper]

Nations classified according to restrictions imposed on export of American AI Chips by American Government 🇺🇸 🌏

[ailatestupdate]

Chinese AI chips

[rjzimmerman]

The Firm That Wants to Power AI With Southern Yellow Pine. (Wall Street Journal)

Excerpt from this Wall Street Journal story:

Power producer Drax DRX 0.48%increase; green up pointing triangle is scouting locations in the American pine belt to build electricity generators fueled by burning wood chips. 

The plan calls for constructing wood-fired power plants in parts of the U.S. South where pulp and paper mills have closed and left timber growers without buyers for those trees unfit for making lumber or poles. 

The plants’ exhaust will be piped underground instead of out of smokestacks, which generates lucrative carbon credits for which Drax is already lining up buyers. 

Plus, there’s the electricity. Technology companies are so eager to run their power-hungry AI data centers without fossil fuels that they’re trying to restart nuclear facilities.

Drax already burns pellets of compressed sawdust in a converted coal-fueled power plant in its home country. Its towering facility in the English countryside produces about 5% of the U.K.’s electricity. Drax has built pellet mills across the southeastern U.S. and in western Canada to feed that plant as well as other wood-burning plants around the world. 

The type of plants it wants to build in the U.S. are known as BECCS, short for bioenergy with carbon capture and storage. They won’t be nearly as large as the U.K. facility. But Drax has set up a subsidiary in Houston called Elimini to build several of them, and signed deals with two of the country’s largest timberland managers to supply the wood. 

“The whole idea is that 24/7 renewable power is going to become increasingly in demand as data centers grow, as AI grows,” Drax Chief Executive Will Gardiner said. “There’s a huge need for that commodity.” 

Elimini’s staff of roughly 150 is studying about 20 locations and aims to have the first plant up and running by 2030, he said. The size of each could vary, but Gardiner said they will likely cost more than $1 billion apiece to build.

[jcmarchi]

MIT engineers grow “high-rise” 3D chips

New Post has been published on https://thedigitalinsider.com/mit-engineers-grow-high-rise-3d-chips/

MIT engineers grow “high-rise” 3D chips

The electronics industry is approaching a limit to the number of transistors that can be packed onto the surface of a computer chip. So, chip manufacturers are looking to build up rather than out.

Instead of squeezing ever-smaller transistors onto a single surface, the industry is aiming to stack multiple surfaces of transistors and semiconducting elements — akin to turning a ranch house into a high-rise. Such multilayered chips could handle exponentially more data and carry out many more complex functions than today’s electronics.

A significant hurdle, however, is the platform on which chips are built. Today, bulky silicon wafers serve as the main scaffold on which high-quality, single-crystalline semiconducting elements are grown. Any stackable chip would have to include thick silicon “flooring” as part of each layer, slowing down any communication between functional semiconducting layers.

Now, MIT engineers have found a way around this hurdle, with a multilayered chip design that doesn’t require any silicon wafer substrates and works at temperatures low enough to preserve the underlying layer’s circuitry.

In a study appearing today in the journal Nature, the team reports using the new method to fabricate a multilayered chip with alternating layers of high-quality semiconducting material grown directly on top of each other.

The method enables engineers to build high-performance transistors and memory and logic elements on any random crystalline surface — not just on the bulky crystal scaffold of silicon wafers. Without these thick silicon substrates, multiple semiconducting layers can be in more direct contact, leading to better and faster communication and computation between layers, the researchers say.

The researchers envision that the method could be used to build AI hardware, in the form of stacked chips for laptops or wearable devices, that would be as fast and powerful as today’s supercomputers and could store huge amounts of data on par with physical data centers.

“This breakthrough opens up enormous potential for the semiconductor industry, allowing chips to be stacked without traditional limitations,” says study author Jeehwan Kim, associate professor of mechanical engineering at MIT. “This could lead to orders-of-magnitude improvements in computing power for applications in AI, logic, and memory.”

The study’s MIT co-authors include first author Ki Seok Kim, Seunghwan Seo, Doyoon Lee, Jung-El Ryu, Jekyung Kim, Jun Min Suh, June-chul Shin, Min-Kyu Song, Jin Feng, and Sangho Lee, along with collaborators from Samsung Advanced Institute of Technology, Sungkyunkwan University in South Korea, and the University of Texas at Dallas.

Seed pockets

In 2023, Kim’s group reported that they developed a method to grow high-quality semiconducting materials on amorphous surfaces, similar to the diverse topography of semiconducting circuitry on finished chips. The material that they grew was a type of 2D material known as transition-metal dichalcogenides, or TMDs, considered a promising successor to silicon for fabricating smaller, high-performance transistors. Such 2D materials can maintain their semiconducting properties even at scales as small as a single atom, whereas silicon’s performance sharply degrades.

In their previous work, the team grew TMDs on silicon wafers with amorphous coatings, as well as over existing TMDs. To encourage atoms to arrange themselves into high-quality single-crystalline form, rather than in random, polycrystalline disorder, Kim and his colleagues first covered a silicon wafer in a very thin film, or “mask” of silicon dioxide, which they patterned with tiny openings, or pockets. They then flowed a gas of atoms over the mask and found that atoms settled into the pockets as “seeds.” The pockets confined the seeds to grow in regular, single-crystalline patterns.

But at the time, the method only worked at around 900 degrees Celsius.

“You have to grow this single-crystalline material below 400 Celsius, otherwise the underlying circuitry is completely cooked and ruined,” Kim says. “So, our homework was, we had to do a similar technique at temperatures lower than 400 Celsius. If we could do that, the impact would be substantial.”

Building up

In their new work, Kim and his colleagues looked to fine-tune their method in order to grow single-crystalline 2D materials at temperatures low enough to preserve any underlying circuitry. They found a surprisingly simple solution in metallurgy — the science and craft of metal production. When metallurgists pour molten metal into a mold, the liquid slowly “nucleates,” or forms grains that grow and merge into a regularly patterned crystal that hardens into solid form. Metallurgists have found that this nucleation occurs most readily at the edges of a mold into which liquid metal is poured.

“It’s known that nucleating at the edges requires less energy — and heat,” Kim says. “So we borrowed this concept from metallurgy to utilize for future AI hardware.”

The team looked to grow single-crystalline TMDs on a silicon wafer that already has been fabricated with transistor circuitry. They first covered the circuitry with a mask of silicon dioxide, just as in their previous work. They then deposited “seeds” of TMD at the edges of each of the mask’s pockets and found that these edge seeds grew into single-crystalline material at temperatures as low as 380 degrees Celsius, compared to seeds that started growing in the center, away from the edges of each pocket, which required higher temperatures to form single-crystalline material.

Going a step further, the researchers used the new method to fabricate a multilayered chip with alternating layers of two different TMDs — molybdenum disulfide, a promising material candidate for fabricating n-type transistors; and tungsten diselenide, a material that has potential for being made into p-type transistors. Both p- and n-type transistors are the electronic building blocks for carrying out any logic operation. The team was able to grow both materials in single-crystalline form, directly on top of each other, without requiring any intermediate silicon wafers. Kim says the method will effectively double the density of a chip’s semiconducting elements, and particularly, metal-oxide semiconductor (CMOS), which is a basic building block of a modern logic circuitry.

“A product realized by our technique is not only a 3D logic chip but also 3D memory and their combinations,” Kim says. “With our growth-based monolithic 3D method, you could grow tens to hundreds of logic and memory layers, right on top of each other, and they would be able to communicate very well.”

“Conventional 3D chips have been fabricated with silicon wafers in-between, by drilling holes through the wafer — a process which limits the number of stacked layers, vertical alignment resolution, and yields,” first author Kiseok Kim adds. “Our growth-based method addresses all of those issues at once.” 

To commercialize their stackable chip design further, Kim has recently spun off a company, FS2 (Future Semiconductor 2D materials).

“We so far show a concept at a small-scale device arrays,” he says. “The next step is scaling up to show professional AI chip operation.”

This research is supported, in part, by Samsung Advanced Institute of Technology and the U.S. Air Force Office of Scientific Research. 

[peterbordes]

Congrates to our TrajectoryVentures.vc portfolio Co’s Groq & LightMatter making the TechRadar 10 hottest AI hardware companies to follow in 2025.

Watch out Nvidia, these startups are looking to dent your dominance.

[fcojperez]

The geopolitics of chips: Nvidia and the AI boom

I’m hooked on The geopolitics of chips: Nvidia and the AI boom on Castbox. Check out this episode! https://castbox.fm/vb/758680204