Google Cuts Jobs, Expands AI Roles

TGIF, everyone! Tech companies are eagerly seeking individuals who not only understand these fundamental processes but can innovate and optimize AI systems. To ready oneself for opportunities in this field, it is essential to have a solid grounding in mathematics, programming, and machine learning concepts. Practical experience with AI frameworks and tools, as well as keeping yourself updated in the latest research and technologies, is equally important. Those who can combine technical expertise with problem-solving skills will find themselves at the forefront of AI.

Here are the 4 interesting AI things that I learned and enjoyed this week.

4 AI Things

AI Research

Google AI's new tool, Patchscopes, helps to explain how AI models think by turning their complex inner workings into simple language we can understand.

1. Feeding Source Prompt to the Source Model: The process begins by inputting a prompt into the AI model, which generates an initial output or hidden state.
2. Transforming Hidden State: This output is then modified or "transformed" to enhance or alter the information it contains, preparing it for further processing.
3. Feeding Target Prompt to Target Model: The modified output is then fed into another AI model or a different part of the same model along with a new prompt targeting specific output requirements.
4. Running Execution on Patched Target: Finally, the AI model processes this information to produce the final output, which now includes insights or explanations derived from the transformed hidden states, aiming to provide clarity on how the model's decision-making process works.

AI News

Tech companies are really into hiring people who know a lot about AI, especially those who've studied a lot (like with PhDs). Big names like Apple, Google, Meta, Microsoft, and OpenAI are looking to fill hundreds of jobs focused on AI. They're not just into doing small projects; they're planning to hire thousands more people. This hiring wave isn't expected to slow down anytime soon, with experts predicting even more growth in AI jobs over the next few years. Also, startups are getting into the game, offering big money to snag top talent from big companies.

AI Concept

This week we are going to talk about Neural Networks. Neural networks mimic the way human brains operate, allowing machines to adapt to new information without being explicitly programmed. Imagine neural networks like a video game, where each level (layer) gets you closer to the final boss (the solution). You start with the first level (input layer), where you feed in all the details (data). As you progress through more levels (hidden layers), the game (network) gets smarter about how to handle the challenges (data) by learning the best moves (patterns). Each level builds on the last, refining strategies (processing data) until you reach the last level (output layer). Here, you face the final boss, and the game gives you the final score or result based on how well everything was played out in the previous levels. Each layer works together, making the network smarter and capable of solving complex problems.

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?? Stay curious, keep questioning.