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Good morning! ☀️ AI is transforming industries—let’s see how it’s reshaping the world around us.
🚀 Here are the latest AI news in a nutshell. Step right up for today's tech sideshow!
Meta's building its own search engine. Zuck wants a piece of Google's pie! 🔍🎯
Generative AI is threatening to create an e-waste tsunami. That's a lot of iPhone-sized problems! 🗑️📱
Apple Intelligence finally lands with iOS 18.1. Siri's getting that promised brain upgrade! 🍎🧠
Google spreading AI Overviews to 100+ countries. The robots are going global! 🌍💫
Andreessen Horowitz's Casado says AI regulation is everyone's problem. Time to pay attention, startups! ⚖️👀
Bret Taylor's startup scores $175M for customer service AI. Because humans answering phones is so 2023! 💰🎭
Vinod Khosla peers into AI's crystal ball. The legendary VCs have visions! 🔮✨
ITI students getting AI career boot camp. Teaching the next gen of robot whisperers! 🎓🤖
Khosla calls SB 1047 author 'clueless.' Tech drama gets spicy! 🌶️🎭
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Meta’s Developing its Own Search Engine to Power its AI Chatbot
Meta is reportedly developing its own search engine to power its AI chatbot, marking a significant shift in its strategy to reduce dependence on current search partners Google and Microsoft Bing. This development represents a crucial step in Meta's broader AI strategy and its competition with other tech giants in the generative AI space.
Evolution of Meta's Search Capabilities
When Meta first introduced its AI chatbot in September 2023, it relied heavily on Microsoft's Bing for web searches, providing context and real-time information to enhance its responses. The company later expanded its capabilities by partnering with Google in April 2024, creating a dual-search approach for its AI system. However, according to reports from The Information, Meta is now working to develop its own web crawler to independently power search queries.
Meta's existing web crawlers have already been gathering information from external websites with increased activity in recent months. This infrastructure could serve as the foundation for their new search engine initiative, though building a comprehensive search system comparable to Google or Bing remains a significant technical challenge.
Strategic Implications and Future Impact
The development of an independent search capability appears to be driven by multiple strategic considerations. Beyond reducing reliance on competitors, Meta's search engine could provide valuable data for training its AI language models. This move aligns with Meta's broader strategy to control its technological destiny in the increasingly competitive AI landscape.
The potential applications extend beyond just powering Meta AI's responses. A proprietary search engine could enhance features across Meta's platform ecosystem, particularly benefiting apps like Threads with real-time news and information integration. This could create a more cohesive and self-sufficient user experience within Meta's family of applications.
However, the project faces substantial challenges. Building a search engine that can effectively crawl, index, and retrieve information from the vast expanse of the internet requires significant resources and expertise. Meta would need to develop sophisticated algorithms for ranking and relevance, while ensuring accuracy and freshness of information.
The timing of this development is particularly noteworthy as competition in the AI space intensifies. With both Google and Microsoft advancing their own AI capabilities, Meta's move to develop independent search capabilities could be seen as a preemptive measure against potential future restrictions from their current search partners.
The project could also have broader implications for the Internet ecosystem. A new major search engine could influence how websites optimize their content, potentially leading to new SEO practices specifically tailored for Meta's crawler. This could create additional considerations for web developers and content creators already managing optimization for multiple platforms.
Meta's search engine development represents more than just a technical project; it's a strategic initiative that could reshape the company's position in the AI and search landscape. While the immediate goal may be to power their AI chatbot, the long-term implications could extend to creating a more integrated and autonomous Meta ecosystem, potentially challenging the current search engine duopoly of Google and Bing.
As this project develops, its success could significantly influence Meta's future direction and its ability to compete effectively in the evolving AI landscape. The outcome may well determine whether Meta can achieve true independence in its AI operations or must continue relying on partnerships with its competitors.
Generative AI could cause 10 billion iPhones’ worth of e-waste per year by 2030
Researchers from Cambridge University and the Chinese Academy of Sciences predict that generative AI could generate annual e-waste equivalent to more than 10 billion iPhones by 2030. Their study projects an increase from 2,600 tons in 2023 to between 400,000 and 2.5 million tons by 2030. While mitigation strategies like repurposing servers and components could reduce waste by 16-86%, the researchers emphasize that achieving lower waste levels depends on industry choices. The study aims to highlight the scale of this challenge rather than limit AI adoption, focusing on the physical waste impact that has received less attention than energy costs.
Apple Intelligence goes live with iOS 18.1 update
Apple has released iOS 18.1, iPadOS 18.1, and macOS Sequoia 15.1, introducing the first wave of Apple Intelligence features. The AI features are only available on newer devices with A17 Pro chips or M1 and later processors. Users must opt-in and join a waitlist for access due to server requirements. The initial release includes writing tools, image cleanup, article summaries, and a new Siri interface. Additional features like Genmoji, Image Playground, and ChatGPT integration will come in version 18.2, currently in developer beta. Apple's approach differs from competitors by using smaller, function-specific models rather than large, general-purpose ones.
📔#1 Insights Today on AI. Click the Links to Read
Google expands AI Overviews in Search to more than 100 countries
Why AI regulation is every startup’s business, with Andreessen Horowitz Martin Casado
Bret Taylor’s customer service AI startup just raised $175M
Vinod Khosla, legendary VC, looks into the past to see the future of AI
ITI students now get a hands-on introduction to careers in AI with a new module
Vinod Khosla calls SB 1047 author ‘clueless’ and ‘not qualified’ to regulate the real dangers of AI
🧑 What specific AI-related skill or knowledge do you want to acquire in the next 6 months?
- I want to learn how to fine-tune large language models for specific applications.
- I'm aiming to master computer vision techniques for my robotics project.
- I want to understand the principles of responsible AI development and implementation.
- I am ready to deploy AI agents into my workflow.
- Other (write it out in the box below)
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💼📈💻Are you currently working on or planning any AI-related projects or startups?
Do you have a business problem that’s been keeping you up at night? Here’s your chance to get it solved! Share your most staggering challenges with us, and I’ll use the power of AI to find solutions tailored just for you. I’ll feature the answers in one of our upcoming Supercharged issues—let’s tackle it together!
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AI is not just about replacing human labor with machines; it's about creating a symbiotic relationship between human expertise and computational capabilities. It's about finding ways to combine the intuition and creativity of humans with the analytical power and pattern recognition of machines.
Sheila Ann McIlraith is a Canadian computer scientist specializing in artificial intelligence. She is a Professor in the Department of Computer Science, University of Toronto.
1-2 sentences about the author or what he does.
⬆️ ️ Trends: How Businesses Implement AI
AI Breakthrough: ChatGPT-Like Model Predicts Dual-Target Drugs for Complex Diseases
In a significant advancement for pharmaceutical research, scientists at the University of Bonn have developed a ChatGPT-like AI model that could revolutionize how we develop drugs for complex diseases. Their groundbreaking research, published in Cell Reports Physical Science, demonstrates how artificial intelligence can predict drugs capable of targeting two different enzymes simultaneously—a capability that could transform the treatment of multifactorial diseases.
The implications are far-reaching. Most serious health conditions, from bipolar disorder and schizophrenia to common cancers and Alzheimer's disease, are complex diseases influenced by a combination of genetic, environmental, and lifestyle factors. Traditional drug development typically focuses on single targets, but this new AI approach opens the door to more sophisticated treatments through polypharmacology—the ability to act on multiple drug targets at once.
At the heart of this innovation is a transformer-based chemical language model, similar to the technology powering ChatGPT. The research team, led by Professor Dr. Jürgen Bajorath and Sanjana Srinivasan, trained their model on over 75,000 pairs of chemical notation strings, known as SMILE strings. These strings act like a molecular alphabet, allowing the AI to understand and predict chemical compounds that can affect multiple targets simultaneously.
The timing couldn't be better. The AI in drug discovery market is projected to reach $13 billion by 2032, according to Statista, reflecting the growing recognition of AI's potential to accelerate pharmaceutical development. This new model represents a significant step forward, demonstrating an ability to exactly reproduce known dual-target compounds even when they were excluded from the training data.
What makes this development particularly exciting is its potential to shrink the drug development lifecycle. By accurately predicting dual-target compounds, the technology could significantly reduce the time and resources needed to develop treatments for complex diseases. It's a perfect example of how AI is transforming the pharmaceutical industry, making drug discovery more efficient and potentially more effective.
The model's success suggests we're entering a new era of drug development, where AI can help us design more sophisticated treatments for the complex diseases that have long challenged medical science. As this technology continues to evolve, it could lead to more targeted, efficient treatments for millions of patients suffering from multifactorial diseases.
⚡ AI Playground: Code & Craft
🛠️ Create Your Own GPT for Personal Use with ChatGPT
What is GPT?
GPT (Generative Pre-trained Transformer) is an AI that creates human-like text by predicting words from patterns it learned in training. You can train it on personal data to fit your specific needs. It’s accessible, even for beginners!
💡 How to Create Your Own GPT
Step 1: Define Your Goal
Decide what task you want your GPT to handle. Be specific!
Example: "I want to create a GPT that helps me draft professional emails."
Step 2: Access ChatGPT
Visit the ChatGPT website, then sign up or log in.
Click Create New to begin.
Step 3: Feed It Your Data
To make your GPT act like a personal copywriter, you’ll need to train it with examples of the type of text you want it to generate.
1️⃣ Collect Content:
Gather emails, articles, or documents you’ve written or like to emulate.
2️⃣ Feed the Content:
Use ChatGPT by copy-pasting your examples into the chat. Give clear instructions, like:
“Here are examples of professional emails I’ve written. Use this style when generating new emails for me.”
3️⃣ Fine-Tune It:
Ask GPT to create new samples. Provide feedback on what you like or want changed to improve its accuracy.
Step 4: Add Your Own Text
Incorporate your style by feeding it specific phrases or templates you often use.
1️⃣ Create a Template:
Provide a sample text with placeholders for customization, such as:
"Dear [Name], I hope this email finds you well. I wanted to follow up on [Topic]. Let me know if you have any questions!"
2️⃣ Set Your Preferences:
Ask GPT to include these templates automatically:
“Use the greeting ‘Hello there,’ in every email and always close with ‘Best regards.’”
3️⃣ Test & Refine:
Run the tool through different tasks—ask it to draft emails, marketing copy, or follow-up notes. Keep refining until the results match your style perfectly.
🔧 This Week’s Tool: GPT by ChatGPT
What is this tool best for?
Creating personalized tools to analyze data, write custom text, and make predictions. It acts like your personal LLM (Large Language Model)—trained on your data to serve your needs.
Why is it better than other tools?
Easy to use, adaptable to personal data, and accessible without advanced skills.
What does it do best?
Generates text, answers questions, summarizes, translates, and supports tasks like writing or coding.
Applications:
💬 Chatbots
📝 Content creation
🌐 Translation
💻 Coding assistance
📧 Personalized writing
📞 Customer support
⚡ Take the Challenge, Make Your GPT, and Win Big! Send us your GPT by Friday!
What is your outcome?
Have an amazing day!
No more playing catch-up. It's time to GET AHEAD!!! 🚀🚀🚀
🙌🏼
Elena
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