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🌟 𝗘𝘅𝗰𝗶𝘁𝗲𝗱 𝘁𝗼 𝗶𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗲 𝗥𝘂𝗻𝘄𝗮𝘆 - 𝘁𝗵𝗲 𝘂𝗹𝘁𝗶𝗺𝗮𝘁𝗲 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗰𝗿𝗲𝗮𝘁𝗶𝘃𝗲 𝘁𝗼𝗼𝗹𝗸𝗶𝘁! 🎨✨ As an AI enthusiast, I'm constantly amazed by the innovative solutions emerging in the tech landscape. Runway stands out as a revolutionary platform that empowers creators to explore the boundless possibilities of AI in their work. Here's why Runway is a game-changer: 1️⃣ 𝗩𝗲𝗿𝘀𝗮𝘁𝗶𝗹𝗶𝘁𝘆: From 𝙜𝙚𝙣𝙚𝙧𝙖𝙩𝙞𝙣𝙜 𝙖𝙧𝙩 𝙖𝙣𝙙 𝙢𝙪𝙨𝙞𝙘 to manipulating videos and 3D models, Runway offers a diverse range of tools to unleash your creativity. 2️⃣ 𝗔𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆: With its 𝙪𝙨𝙚𝙧-𝙛𝙧𝙞𝙚𝙣𝙙𝙡𝙮 𝙞𝙣𝙩𝙚𝙧𝙛𝙖𝙘𝙚 and intuitive design, Runway makes AI accessible to creators of all skill levels, democratizing the creative process. 3️⃣ 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻: 𝘾𝙤𝙣𝙣𝙚𝙘𝙩 𝙬𝙞𝙩𝙝 𝙡𝙞𝙠𝙚-𝙢𝙞𝙣𝙙𝙚d individuals in the Runway community, exchange ideas, and collaborate on projects to push the boundaries of what's possible. 4️⃣ 𝗖𝘂𝘁𝘁𝗶𝗻𝗴-𝗘𝗱𝗴𝗲 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆: Runway harnesses the latest advancements in AI, including 𝙙𝙚𝙚𝙥 𝙡𝙚𝙖𝙧𝙣𝙞𝙣𝙜 and generative models, to inspire and empower creators to think outside the box. Whether you're a digital artist, filmmaker, musician, or designer, Runway provides the tools you need to turn your 𝙫𝙞𝙨𝙞𝙤𝙣 𝙞𝙣𝙩𝙤 𝙧𝙚𝙖𝙡𝙞𝙩𝙮. Join the AI revolution and unlock new dimensions of creativity with Runway! https://runwayml.com #AI #Creativity #Innovation #runway #runwayml #generatingart #deeplearning

Great to chat with Paul Gray at Tender Copilot about what's happening in the world of AI and the range of options available, rebids and leadership. Particularly interesting to talk about about supporting SMEs with usable, affordable AI bidding software to get quality first drafts quickly. And about helping SMEs to quickly implement, with ongoing support to keep core 'bid library' material up to date. Bigger clients with their own full time bid teams seem more able to keep the company materials AI uses moving forward themselves. But interesting to see how smaller organisations with limited bid resource can also be helped.

Everyone is so excited about AI (Generative AI specifically), but if you knew it could further accelerate the warming we are seeing in our environment today, would you still happily use it to write social media posts or articles? Seriously, based on what I’ve found, we must consider hanging back progress here and only use AI in areas where we can make meaningful improvements for all life on our planet, because if we don’t, well… We also need to get on top of e-waste, because by 2030 there will be even more e-waste in our environment, while at the same time, recycling rates are expected to go down! It’s beyond time to get on top of this crisis, because it’s already out of hand and doing so much harm. This is an important and complicated topic – we need to look it all in the eye #ClimateEmergency #AI #ewaste #OneBillion #UncommonCourage https://lnkd.in/gSBtP5f5

Many news stories about artificial intelligence (AI) solutions cite a comparison of the rate of technological development and government regulation. The reason for including this comparison in one of these news stories, though rarely explicit, appears to me to be the following: readers need to be aware of these rates; public safety will be affected one way or another; a balanced pace (where the meaning of the word balanced might vary from reader to reader, not to mention the view of the writer) is best, but if something less-than-best is in the offing, then readers need to be aware of it.   But, with respect, should we, as readers of these stories, be asking the news reporters and their editorial teams to include these comparisons in a more thoughtful way?   I think so. Here is why: There is little the US general public can do about imbalances in these rates beyond notifying their public officials, looking for changes in the pace of regulatory activity and, if required, voting for new representatives who will, presumably, do a better job at getting regulatory activity to happen faster, or slower, depending on a given reader's political viewpoint.   Highlighting these imbalances only increases the odds readers will come away from one of these stories with an emotional - certainly not rational - response.   Case in point?   https://lnkd.in/eg7iDj4q   What do other writers and readers think?   #newswriting #technologyvsregulation #selfdrivingtrucks 

Can a single-stage diffusion model revolutionize grasp synthesis by boosting speed and diversity? 🤔 Discover how FastGrasp outperforms traditional methods with superior pose quality! 🚀 #AI #Robotics #Innovation

Are you wondering about AP Automation? Put those wonders away and join us, David Geier from Jacob Stern & Sons, Inc., and Mikko Hytönen from Dooap as we talk AP Automation, how it transforms a organization (from parchment to AI) and we seem to have fun along the way! https://lnkd.in/g_diW2MM

AI: It’s the Car and the Driver I recently found an old box of photos from the 1970s, including some of my dad’s Alfa Romeos. He loved restoring those cars meticulously—but also drove them. Hard. He totaled one within a year of buying it. That got me thinking about AI and race cars. - Some people are drawn to shiny, exciting new tech. - Others focus on the speed and productivity it brings to their work. - Others appreciate the precision—how AI can help them think more clearly, solve challenges, or create something entirely new. Whether it’s a high-performance car or a cutting-edge AI tool, if you don’t know how to handle all that power, you’re going to miss half of what’s possible—or worse, crash. Some Challenges of Driving AI: Most teams use AI in ad hoc, unstructured ways. Tools like HubSpot, Perplexity, and Grammarly are helpful, sure—but without a clear direction or strategy, AI becomes a patchwork of isolated solutions. Here’s what happens: - Beige outputs: Technically correct but forgettable. - Missed opportunities: The real potential of AI—like scaling your work or unlocking creativity—never gets realized. - Winning the lap but losing the race: Short-term gains without long-term momentum. It’s Not Just About Speed—It’s About Handling As the saying goes, “It’s not the car, it’s the driver.” Well, the car matters too. When it comes to AI, most people aren’t great drivers yet—and don’t even realize they need to learn. With the right tools, skills, and mindset, AI doesn’t just make you faster—it helps you win the race. >> Are You Ready to Take the Wheel?

Interesting / powerful summary

The building multimodal search and RAG systems course from DeepLearning.AI covers implementing RAG with multimodal data, from contrastive learning and any-to-any search to visual instruction tuning and end-to-end multimodal RAG systems. Industry applications have been explored and multi-vector recommender systems were created. As AI increasingly processes multiple data modalities, developers can learn key skills in embedding, retrieving, and generating across different modalities to build smarter search, RAG, and recommender systems. #MultimodalAI #RAG #MachineLearning https://lnkd.in/giX6HxU2