- 4 AI Things
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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.
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.
Transforming Hidden State: This output is then modified or "transformed" to enhance or alter the information it contains, preparing it for further processing.
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.
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.
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.
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.
Exclusive Content
As Google moves jobs to India and Dublin to cut costs, there's a mad dash in Europe and India with everyone trying to land a role. It's common in the tech industry for advancements in AI and automation to lead to restructuring, as companies may streamline operations or shift focus towards new technologies. It's like a bizarre game of musical chairs, but instead of sitting down, everyone's updating their LinkedIn profiles!
The CEO of Anthropic predicts that within a few years, AI could become completely autonomous. He's concerned about the power such AI could give to certain countries, potentially upsetting global stability. However, despite the futuristic and somewhat alarming scenario, he admits there's still uncertainty and his predictions might not pan out exactly as expected.
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⏭️ Stay curious, keep questioning.