QiML 2.0: Speed-Ups, Scalability, and Performance for New Machine Learning Era Event Seminar and PDF 02/22/24.
Steve Jobs, Apple Inc. Co-founder stated: “One of the things I’ve always found is that you’ve got to start with the customer experience and work backwards for the technology. You can’t start with the technology and try to figure out where you’re going to try to sell it.”
The attached event seminar is a technology conclusion regarding the practical use of QiML 2.0 Classical machine learning. Table 1 illustrates the new product's purpose which allows for speed-ups, scalability, and performance over existing quantum-inspired software. 8 examples of quantum machine learning algorithms dequantized into feasible classical algorithms is also included.
Several 2024 Tensor network papers were reviewed, highlighted by the Multiverse CompactifAI tensor network that compressed a familiar 7 billion parameter LlaMa Large language model to 30% of its size maintaining over 90% accuracy, with a retraining time that was at least 2x faster.
Next steps for the startup include identification within specific areas from below that could improve patient experience the most using QiML 2.0 AI.
- Higher level of care is received
- Faster results exceed expectations
- Value of service is economical
- Human-AI team environment is welcoming