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Neural Networks Achieve Human-Like Language Generalization

Unite.AI

In the ever-evolving world of artificial intelligence (AI), scientists have recently heralded a significant milestone. They've crafted a neural network that exhibits a human-like proficiency in language generalization. ” Yet, this intrinsic human ability has been a challenging frontier for AI.

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Majority of AI Researchers Say Tech Industry Is Pouring Billions Into a Dead End

Flipboard

Given that AGI is what AI developers all claim to be their end game , it's safe to say that scaling is widely seen as a dead end. The premise that AI could be indefinitely improved by scaling was always on shaky ground. Of course, the writing had been on the wall before that.

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Getting ready for artificial general intelligence with examples

IBM Journey to AI blog

Most experts categorize it as a powerful, but narrow AI model. Current AI advancements demonstrate impressive capabilities in specific areas. A key trend is the adoption of multiple models in production. This multi-model approach uses multiple AI models together to combine their strengths and improve the overall output.

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This AI Tool Explains How AI ‘Sees’ Images And Why It Might Mistake An Astronaut For A Shovel

Marktechpost

However, the precise mechanisms behind these processes remain elusive, resulting in a black-box model. Thus, there is a growing demand for explainability methods to interpret decisions made by modern machine learning models, particularly neural networks.

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Types of central processing units (CPUs)

IBM Journey to AI blog

Now GPUs also serve purposes unrelated to graphics acceleration, like cryptocurrency mining and the training of neural networks. Microprocessors The quest for computer miniaturization continued when computer science created a CPU so small that it could be contained within a small integrated circuit chip, called the microprocessor.

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A Critical Look at AI-Generated Software

Flipboard

ChatGPT, by itself, is just a natural-language interface for the underlying GPT-3 (and now GPT-4 ) language model. But what’s key is that it is a descendant of GPT-3, as is Codex, OpenAI’s AI model that translates natural language to code. This same model powers GitHub Copilot, which is used even by professional programmers.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

This led to the theory and development of AI. IBM computer scientist Arthur Samuel coined the phrase “machine learning” in 1952. In 1962, a checkers master played against the machine learning program on an IBM 7094 computer, and the computer won. He wrote a checkers-playing program that same year.