New course with CrewAI! João (Joe) Moura is back to help you explore how multi-agent systems are used in real businesses today and how to improve them through performance testing and human feedback. You'll create crews, organize them into workflows, and build pipelines for more efficient automation. Here's a peek at what you’ll build: 📅 An automated project planning crew that breaks down projects and allocates resources. 📊 A report generator that interacts with project management tools like Trello. 💼 A sales pipeline agent that enriches leads and drafts personalized emails. 🛠️ A customer support analysis pipeline that creates issue reports and visualizations. 📝 A content creation crew that researches online, uses RAG to generate content, and refines it. Enroll for free: https://hubs.la/Q02VtSXK0
DeepLearning.AI
Software Development
Palo Alto, California 1,084,374 followers
Making world-class AI education accessible to everyone
About us
DeepLearning.AI is making a world-class AI education accessible to people around the globe. DeepLearning.AI was founded by Andrew Ng, a global leader in AI.
- Website
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http://DeepLearning.AI
External link for DeepLearning.AI
- Industry
- Software Development
- Company size
- 11-50 employees
- Headquarters
- Palo Alto, California
- Type
- Privately Held
- Founded
- 2017
- Specialties
- Artificial Intelligence, Deep Learning, and Machine Learning
Products
DeepLearning.AI
Online Course Platforms
Learn the skills to start or advance your AI career | World-class education | Hands-on training | Collaborative community of peers and mentors.
Locations
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Primary
2445 Faber Pl
Palo Alto, California 94303, US
Employees at DeepLearning.AI
Updates
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🔧 Question for Developers: How are you currently integrating AI into your software development workflow? AI is transforming the way we code, but we all approach it differently. Are you using AI for code generation, debugging, or perhaps for something more innovative? Share your experiences and tips in the comments! Interested in expanding your AI toolkit? Our new skill certificate on Generative AI for Software Development might have just what you need. Explore it now: https://hubs.la/Q02Wf9yK0
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Researchers at Kuaishou Technology and two Chinese universities introduced Pyramidal Flow Matching, a technique that reduces processing requirements for training video generators. Using this method, they developed an open source text-to-video model and plan to release the training code. The system combines a pretrained image generator, an autoencoder, and text encoders (T5 and CLIP). By downsampling and upsampling video frame embeddings during the training process, it significantly reduces computation. Read our summary of the paper in #TheBatch: https://hubs.la/Q02W3MQp0
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Twice a week, Data Points brings you the latest AI news, tools, models, and research in brief. In today’s edition, you’ll find: 🎥 Allegro: an open-source video generation model from Rhymes AI 🤖 Meta’s new quantized Llama 3.2: 1B and 3B model versions 💧 SynthID text: a new text watermarking tool 🛠️ Lingua and Self-Taught Evaluator: Meta’s model-training tools Read the full issue and subscribe to #DataPoints now: https://lnkd.in/di7aXb3b
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Data engineering can be tough to break into—most companies don’t hire junior roles. Many start as software engineers or data analysts. Zach Wilson began his journey in a software engineering role himself! Learn more about his path in the Data Engineering professional certificate: https://hubs.la/Q02W0yV90
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Amazon, Google, and Microsoft announced investments in nuclear energy projects to meet AI infrastrucuture's growing energy demands while reducing carbon emissions. 💼 Amazon is partnering with X-energy to develop and deploy small modular reactors in the U.S. 🔍 Google is collaborating with Kairos Power to build similar technology. ⚛️ Microsoft signed a deal to restart a nuclear plant at Pennsylvania’s Three Mile Island. Learn more in #TheBatch: https://hubs.la/Q02W1y6q0
Amazon, Google, and Microsoft Bet on Nuclear Power to Meet AI Energy Demands
deeplearning.ai
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We are proud to support the AI for Climate Matching Day on November 20th, where 30 inspiring nonprofits will showcase different AI solutions designed to combat climate change. 🔗 Learn more and register: https://lnkd.in/dTnN6fsx
Picture this. It's 2050. The world has just celebrated a major milestone in the fight against climate change. And it all started with a 90-minute event back in 2024. On November 20th, 2024, AI innovators worldwide will gather for the AI for Climate: Matching Day 🙌 In just 90 minutes, you'll witness: • 10 rapid-fire pitches from visionary organizations • Ideas ranging from AI-powered reforestation to smart energy grids • Your chance to be part of world-changing climate solutions The clock is ticking. Climate change won't wait, and neither should you. Your AI skills could be the missing piece in one of these green puzzles. Be part of the story that changes our planet's future. Register now. Your future self will thank you 👉https://lnkd.in/dzErGP63 #AIforClimate #AIforChangemakers #BeTheChange
Join AI for Climate Matching Day!
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#AIPythonforBeginners has equipped learners with practical Python skills. From automating tasks and improving efficiency to integrating LLMs into the process, learners all over the world are applying these skills in impactful ways. Swipe through to read their thoughts on this course series led by Andrew Ng. Ready to get started? Sign up for free: https://lnkd.in/ezbn6iwm
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Mistral AI introduced two new local device-sized language models, Ministral 3B and Ministral 8B. Available in base and instruction-tuned versions, these models outperform similar-sized models from Google and Meta across benchmarks in knowledge retrieval, reasoning, and multilingual tasks. Both models can process 131,072 tokens and enable function calling to connect with other tools, APIs, and data sources. Learn more in #TheBatch: https://lnkd.in/eBS5vcKu
Mistral AI Unveils Ministral 3B and 8B Models, Outperforming Rivals in Small-Scale AI