2.75 BILLION:
https://www.anthropic.com/

Artificial Intelligence (AI) Terms:

1. Machine Learning (ML): A subset of AI that enables systems to learn and improve from experience without being explicitly programmed.
2. Deep Learning: A type of machine learning that uses neural networks with many layers to learn representations of data.
3. Neural Networks: Computational models inspired by the structure and function of the human brain, used in machine learning and deep learning.
4. Natural Language Processing (NLP): A branch of AI focused on enabling computers to understand, interpret, and generate human language.
5. Computer Vision: The field of AI that enables computers to interpret and understand visual information from the real world.
6. Expert Systems: AI systems designed to mimic the decision-making ability of a human expert in a particular domain.
7. Reinforcement Learning: A type of machine learning where an agent learns to make decisions by interacting with an environment and receiving feedback in the form of rewards or penalties.
8. AI Ethics: The study of ethical issues arising from the development and deployment of AI systems.
9. AI Bias: Unintended or unfair outcomes in AI systems due to biased data or algorithms.
10. AI Safety: Concerns and research focused on ensuring that AI systems operate safely and do not pose risks to humanity.
11. AI Governance: Policies, regulations, and frameworks for the responsible development and use of AI.
12. AI Explainability: The ability of AI systems to explain their decisions and actions in a human-understandable manner.
13. AI Robustness: The resilience of AI systems to adversarial attacks or unexpected inputs.
14. AI Applications: Various domains and industries where AI technologies are applied, including healthcare, finance, transportation, and more.
15. AI Research: Ongoing scientific exploration and development of AI techniques, algorithms, and methodologies.

Artificial General Intelligence (AGI) Terms:

1. Artificial General Intelligence (AGI): AI systems with the ability to understand, learn, and apply intelligence across a wide range of tasks and domains, similar to human intelligence.
2. Singularity: A hypothetical future event where AI surpasses human intelligence, leading to unpredictable changes in society and civilization.
3. Friendly AI: AGI systems designed with values aligned with human interests and goals to ensure they act in a beneficial and cooperative manner.
4. Alignment Problem: The challenge of ensuring that AGI systems are aligned with human values and goals to avoid unintended consequences or harm.
5. AGI Safety: Research and efforts focused on developing safe and beneficial AGI systems that align with human values.
6. Moravec’s Paradox: The observation that tasks requiring high-level reasoning are often easier for humans but difficult for AI, while tasks requiring low-level sensorimotor skills are often easier for AI but difficult for humans.

These terms represent just a subset of the extensive terminology and concepts within the fields of AI and AGI, which continue to evolve as research progresses.

Mar 21, 2024 #WSJ#Neuralink#TechElon Musk’s Neuralink recently implanted a chip in a human for the first time. The emerging market of brain computer interfaces, or BCIs, is in the process of finding its footing. In a world where AI is on the rise, BCIs allow for telepathic control of computers and wireless operation of prosthetics. But how does this tech work? WSJ goes inside a brain surgery to see how the implants work, and breaks down what it’s going to take to get these devices on the market. Chapters: 0:00 Musk’s Neuralink 0:41 The market 3:03 Synchron 3:57 Precision 5:16 What’s next? News Explainers Some days the high-speed news cycle can bring more questions than answers. WSJ’s news explainers break down the day’s biggest stories into bite-size pieces to help you make sense of the news. #Neuralink#Tech#WSJ

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