- Knowledge is power.
- Sir Francis Bacon (note Thomas Jefferson often used the expression.) "Great minds think alike." To which I think fits here. This is attributed to Carl Theodor Von Unlanski.
"Everyone's talking about AI now..."
Dear Reader, that is all it is, talk. I see the computer producers claiming AI assistance. These computers are just more efficient versions of past offerings. They are quicker with more storage, but everything else is just PR. AI is in pre-season like in the NFL. It is getting better, but it will take time. Do you recall the propaganda around the famous chess match between grandmaster Gary Kasparov and IBM's Deep Blue? Gary won the first time, but the computer beat him the following year. Chips do "learn" from their past mistakes unlike many humans. The real question is who benefits and what and where AI will be implemented?
Founder...
Berners-Lee who invented the worldwide web says, "AI is an agent like a valet of the rich." We, at Evolution fear that AI will be like the atomic bomb in the next global war. However, the actual AI thing is really a work in progress. Every nation and firms are seeking its power. One big problem that they all missed is that in developing these data centers, AI requires a lot of energy and water. Too many locations were chosen far from populations. The firms were seeking easy permitting. Now, they discover not enough water or electrical power. Meta, to which we mentioned in a previous piece, purchased a defunk nuclear plant to get energy. I find giving a firm who cannot control their own platform the right to operate a nuclear plant, very troublous for our safety. What is not mentioned is that data centers need power, a lot of power. In any area where new data centers are developed, consumers will suffer higher energy bills. President Trump is wrong on alternative energy. We need all sources. This is not oil versus clean, but low priced energy for all. Meanwhile,
Recent Success
IBM developed the smalest transistor. Amazon is developing their data centers that have new and better chips like Tranium and Inferentia. These two chips use less water and are highly efficient. Google's Deep Mind , uses the web as an aid to its AI chip. Remember all the hoopla around China's Deep Seek? It is just BS like we stated in our opening paragraph. With that said, we must acknowledge the great contributions from early transistors and today's chips. This led to our cell phones, drones and a host of developments in our appliances, cars and life. However, the latest from business leaders and scientists suggest concerns to our economy as AI can replace humans in many functions like paralegals, surgery, transportation and moving of product with robotic carts. Robots have secured their place in auto manufacturing and in warehouses. AI, along with drones have been fabulous for agriculture. It has become a must for satellites and weather forecasting.
The billionaire, Sam Altman and AI's "godfather, Geoffrey Hinton both warned about the loss of jobs due to AI and they feel it will widen the wealth gap. The two advocate a basic universal income. Ray Dalio says, "AI is a great tool, but it presents dangers for workers." He also believes it will worsen the wealth gap. To us, at Evolution, this type of serious economic problems could lead to social unrest and we have enough kindling floating around as it is right now. With all of the above, the modern truth comes from the great American, Gordon Moore. He co-founded Fairchild Semiconductor and Intel. He stated...
Moore's Law
In 1965 he said, "That the number of transistors in an integrated circuit (IC) doubles about every two years." His observation held true, but when numbers go to infinity, no one can give an accurate answer. The problem is the capability to continue to design chips that make progress possible. This has led scientist to declare Moore's Law is dead. Evidence can be seen through the timeline of advancements in improvements in the field. The last step forward took over five years. In building these new data centers, the producers are finding that costs are high as well as energy and water needs.
Top scientists say that future gains well come from software, algorithms and hardware architecture. There is also another concern, coding. What works for one program may not be the most efficient in another like 3D integration, photonic computing, carbon nanotube transistors and neuromorphic computing (We have no idea what that is?)...Peace
