C3AI 17 min Pattern Search. Earnings Watch
C3AI is a stock I am watching as it is a company I am watching. The world in front of us will be more and more run by machines and machines will be run by AI. When I see campaigns to lower a companies stock and the company does not flinch I also take notice. This is a new field with high risk. So crises money exits. But I believe this is a contender for “I wish I would have bought this under 50". I also prefer long-term investments to not be at the end of their life expectancy. That is better for short-term trades. I have watched this company go from small partnerships to full integrations. Integrations are much stronger than partnerships. C3AI is embedding itself into the operations management of the AI aspect of a machine-run world. Integrating is major when we are looking at machine learning. This embeds an early entry company into a market that requires time to learn. Replacing old systems and competition will be important where I look to see an emerging market for the data acquired function through time especially in the design of new sensors lower friction actuators and such. Google AI just used this technology in a virtual environment to solve imbalances in a plasma stream hotter than the core of the sun. This is the fusion reactor that is going to change the world. It would not be possible without systems like C3AI. this is the actual "Floor boss" of the machines. keeping every pulse and mechanism in a very specific state at a very precise moment and place in space-time.
Latest success from Google’s AI group: Controlling a fusion reactor
The AI was trained on a simulator to shape the plasma held within a tokamak.
JOHN TIMMER - 2/16/2022, 4:54 PM
Excerpt
"Developing the control software for a tokamak is a complicated process. Based on past experience with similar designs, engineers can extract some of the basic principles needed for the software to function, like what sensor inputs to read and how to respond to changes in them. But there are always quirks based on the design of the hardware and energies of the plasma being used. So, there tends to be an iterative process of measuring and modeling, followed by tweaks to the control process, all the while keeping the performance sufficient to make adjustments in near real-time. The resulting control software tends to be fairly specialized. If researchers want to experiment with a very different geometry for the plasma in the tokamak, a significant revision to the software may be required.
Researchers in the field had already identified artificial intelligence as a possible solution. Give the right AI sufficient examples, and it could figure out which control configurations produce the desired properties in the plasma. That would free people to focus on the desired end-state they wanted and then just let the software produce it for them so that they could study it. An AI should also be more flexible; once it is trained on how to control the system, it should be able to produce very different plasma configurations for study without the need for reprogramming."
From Google AI
"C3 AI’s applications leverage Google Cloud’s infrastructure and data engines and both companies’ AI/ML capabilities."
From C3AI
"C3 AI Data Fusion
C3 AI Data Fusion integrates, unifies, and de-conflicts disparate operational data sources and uses AI to enable effective and timely decision making in the field."
Latest success from Google’s AI group: Controlling a fusion reactor
The AI was trained on a simulator to shape the plasma held within a tokamak.
JOHN TIMMER - 2/16/2022, 4:54 PM
Excerpt
"Developing the control software for a tokamak is a complicated process. Based on past experience with similar designs, engineers can extract some of the basic principles needed for the software to function, like what sensor inputs to read and how to respond to changes in them. But there are always quirks based on the design of the hardware and energies of the plasma being used. So, there tends to be an iterative process of measuring and modeling, followed by tweaks to the control process, all the while keeping the performance sufficient to make adjustments in near real-time. The resulting control software tends to be fairly specialized. If researchers want to experiment with a very different geometry for the plasma in the tokamak, a significant revision to the software may be required.
Researchers in the field had already identified artificial intelligence as a possible solution. Give the right AI sufficient examples, and it could figure out which control configurations produce the desired properties in the plasma. That would free people to focus on the desired end-state they wanted and then just let the software produce it for them so that they could study it. An AI should also be more flexible; once it is trained on how to control the system, it should be able to produce very different plasma configurations for study without the need for reprogramming."
From Google AI
"C3 AI’s applications leverage Google Cloud’s infrastructure and data engines and both companies’ AI/ML capabilities."
From C3AI
"C3 AI Data Fusion
C3 AI Data Fusion integrates, unifies, and de-conflicts disparate operational data sources and uses AI to enable effective and timely decision making in the field."
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