Jagdish Repaswal

🚀 Meta AI Chatbot, powered by Meta Llama 3 LLM, has finally arrived in India! 🌟🤖 Meta AI Chatbot is an advanced NLP system that leverages the powerful Llama 3 LLM, capable of understanding and responding to user queries across multiple platforms. Technical Highlights: 1. Powered by Llama 3 LLM: Trained on a vast amount of text data, enabling it to handle complex conversations, understand context, and reply with accurate answers. 2. Multilingual Support: The chatbot supports multiple languages, including English, Hindi, Tamil, and more. Users can seamlessly switch between languages based on their preferences. 3. Integrated Across Multiple Platforms: Available on WhatsApp, Facebook, Messenger, Instagram, and meta.ai, this chatbot promises to revolutionize how we interact with technology. How You Can Use This Chatbot: - Interact on Topics of Interest: The chatbot will analyze your query and provide relevant information. - Recommendations and Summaries: Get recommendations, summaries of key tech news, and business insights. 🚀𝗨𝘀𝗲 𝗖𝗮𝘀𝗲𝘀: 1. 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗦𝘂𝗽𝗽𝗼𝗿𝘁: Integrate the chatbot into customer support systems to handle common queries, provide troubleshooting steps, and escalate complex issues to human agents. 2. 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗥𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀: The chatbot can analyze user preferences and recommend personalized content such as articles, videos, or podcasts. 3. 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝗰𝗲: Students can ask questions related to their coursework, research, or exam preparation. 4. 𝗠𝗮𝗿𝗸𝗲𝘁 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: Entrepreneurs and product managers can gather insights on market trends, competitor analysis, or consumer behaviour. 5. 𝗖𝗼𝗱𝗲 𝗧𝗿𝗼𝘂𝗯𝗹𝗲𝘀𝗵𝗼𝗼𝘁𝗶𝗻𝗴: Developers can seek help with debugging code, understanding error messages, or exploring best practices. 6. 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗧𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗶𝗼𝗻: Users can input phrases in one language, and the chatbot can provide translations. 7. 𝗖𝗮𝗿𝗲𝗲𝗿 𝗚𝘂𝗶𝗱𝗮𝗻𝗰𝗲: Professionals can discuss career paths, skill development, and job market insights. I reiterate that the adoption of AI will accelerate when these capabilities are available at the edge. Meta AI Chatbot is the latest addition in this space where a common user will be able to leverage the power of AI. #MetaAI #Llama3LLM #AIChatbot #NLP #Technology #CustomerSupport #ContentRecommendations #Education #MarketResearch #CodeHelp #LanguageTranslation #CareerGuidance #AIatEdge 🌐✨

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The Art of the VC Pitch: A Brief Guide to Maximizing Your Chances With Venture Capital Through Giving Better Pitches Pitching to a Venture Capital firm is different from any other kind of pitch. It's not like a sales pitch, a product pitch, or any other kind of presentation. This guide is a road map to the nuts and bolts of maximizing your opportunity when you manage to get in front of VCs

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Brilliant write-up of another MOVEit SFTP server bug. The essential idea behind this multi-pronged exploit: a) Upload a public key to the target SFTP server to a known location. How? Simple: Exploit server logging :-) The researchers found that the server logged copiously. So they found an unauthenticated endpoint meant for guest users and supplied the key as payload. The server dutifully logged the key contents into the log file. Now because key files MUST begin with the ----- BEGIN PUBLIC KEY ----- text, the researchers needed to find a key format that the SFTP server accepted that would accept any file and strip out the contents until it found a valid key. They found it in the PPK format (Putty keys). So they converted their key to this format, then invoked the endpoint with the PPK key as payload and voila their public key is now resident in a log file on the target server. b) Now authenticate as a user on the target server except that you provide the path to the log file containing the public key in the previous step. Sign this request with the same key.  c) This authentication will succeed despite attacker not knowing the keys of the user being impersonated. This occurs because of a bug in how the authentication is handled and the interplay with a lower level SSH library being used. The researchers seem to imply that code reviews may have caught this bug. But it's not so simple. Fuzz testing would indeed have caught this and certainly code coverage driven testing because an error in one code path was exploited to trigger a bug in another. A final point: It's hard to see why the entire payload needs to be logged, or even why sensitive data like keys (even if public keys) are not masked.  Read this excellent write-up - link in comments - and get ideas on the ways attackers think - as better ways to secure your own code.

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Open the LLM hood! Google offers a great 5 day GenAI intensive course. What's being covered? Day 1: Foundational Models & Prompt Engineering - Explore the evolution of LLMs, from transformers to techniques like fine-tuning and inference acceleration. Get trained with the art of prompt engineering for optimal LLM interaction. Day 2: Embeddings and Vector Stores/Databases - Learn about the conceptual underpinning of embeddings and vector databases, including embedding methods, vector search algorithms, and real-world applications with LLMs, as well as their tradeoffs. Day 3: Generative AI Agents - Learn to build sophisticated AI agents by understanding their core components and the iterative development process. Day 4: Domain-Specific LLMs - Delve into the creation and application of specialized LLMs like SecLM and Med-PaLM, with insights from the researchers who built them. Day 5: MLOps for Generative AI - Discover how to adapt MLOps practices for Generative AI and leverage Vertex AI's tools for foundation models and generative AI applications. Here are the notebook building of Gemini models: https://lnkd.in/eUhqpyu7 To register: https://lnkd.in/e5DSvHXW

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🚀 How the World's Biggest Startups De-risked Their Businesses from Pre-Seed to IPO 👇 🥜 Pre-Seed Stage: Dropbox 🔺Problem: Idea validation and technical feasibility. 🔹Solution: Drew Houston created a simple demo video showcasing seamless file synchronization. 🔻Derisking: The video quickly garnered attention, validating the concept without heavy initial investment. 🌱 Seed Stage: Airbnb 🔺Problem: Product-market fit and initial customer acquisition. 🔹Solution: Founders rented out air mattresses to conference attendees and manually recruited hosts and guests. 🔻Derisking: They iterated based on early user feedback, proving a viable market for their model. 🌿 Series A: Instagram 🔺Problem: Scaling the product and user engagement. 🔹Solution: Pivoted from Burbn to a streamlined photo-sharing platform with filters. 🔻Derisking: Narrowing focus led to rapid user adoption, attracting Series A funding from Benchmark Capital. 📈 Series B: Slack 🔺Problem: Proving scalability and sustaining user growth. 🔹Solution: Invested in infrastructure and integrated with third-party applications. 🔻Derisking: Ensured scalability and added value through integrations, maintaining growth momentum and securing Series B funding. 🚀 Series C: Uber 🔺Problem: Expanding market presence and overcoming regulatory challenges. 🔹Solution: Expanded aggressively to new cities while lobbying and negotiating with regulators. 🔻Derisking: Proactive regulatory approach and rapid market expansion demonstrated growth potential, securing Series C investment. 🌎 IPO or Exit Stage: Facebook 🔺Problem: Ensuring regulatory compliance and maintaining growth trajectory. 🔹Solution: Invested in corporate governance, transparency, and compliance measures. 🔻Derisking: Focused on financial performance and regulatory concerns, facilitating a successful public offering. Startups, take note! 🎯 These strategies can help you navigate your growth journey from pre-seed to IPO.🌟 ~~~~~~~ Based on a post shared by: Guillermo Flor ♻️Repost to inspire your Startup Network💡 LinkedIn: Dr. Michael Tadros Agile | PMP® | cPgM® | BSc. | MSc. | PhD. #startup #startups #michael_theprofessor #startupfunding #success #research #partnerships #fundraising #investing #entrepreneurlife #innovation #founders #projectmanagement #smallbusiness #entrepreneurship #entrepreneur #entrepreneurs #venturecapital #investment #venturecapital #siliconvalley #technology

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This hard reset is required for all AI founders from India building global B2B products: Product Innovation > GTM muscle Product innovation is happening at a rapid pace in each of your categories, valley competitors are building thought through features that can help them win customers mid-long term, GTM muscle alone without product differentiation wont help you win in the first half of this AI decade. We are doing this hard reset within BoldCap on what we are looking for in AI founders. Ping us if you are tinkering in global AI B2B products. Shiv Tayal Pratham Chadha Aditi Gera

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Apple Intelligence is a fascinating example of thoughtfully designing an AI ecosystem to deliver a great user experience. Apple's design and tradeoffs hold lessons for every enterprise building AI applications. Here are six key insights: 1. **Strategic Fit**: Apple leverages AI to enhance its strategic device and app store advantages while focusing on privacy and user trust. How can you build an AI system that also builds competitive advantage? 2. **Focused Use Cases**: Apple targets everyday tasks that can be performed mostly on-device, emphasizing privacy and efficiency. What use cases can you reliably deliver to delight customers? 3. **Customized Technology Stacks**: Apple uses a combination of on-device models and its own cloud infrastructure to balance performance, privacy, and cost. What are your performance criteria, and how are you designing your AI systems to meet them? 4. **Right LLMs for the Job**: Apple employs different model tiers, including a 3B parameter model for on-device tasks and a 70B parameter model for more complex queries, with OpenAI's GPT-4o as a fallback. What models best fit your use cases, and are you building a flexible architecture to accommodate future LLM progress? 5. **Grounded in Data**: Apple’s models use personal data stored on the device to provide more contextual and accurate responses. How are you curating and leveraging your unique data to deliver the best responses? 6. **Privacy**: Apple ensures privacy through on-device processing and secure cloud infrastructure, with user consent required for queries handled by OpenAI. How are you securing data and ensuring you build trust with users? Apple’s approach will likely set a standard for privacy-focused AI consumer applications. Their approach also provides a clear roadmap for other B-B and B-C companies investing in AI solutions.

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Head-to-Head: Dark Horse Xdash AI vs. OpenAI's Billion Dollars GPT 4o - What a Competition? "To maintain neutrality and ensure a fair evaluation, a complex prompt was generated by another powerful LLM and subsequently tested by the same LLM." Folks, just imagine a competition between two super-smart machines! # The Challenge: Brain Power Test! Both AI's (GPT 4o and Xdash AI) were given a same complex task that required them to understand things, be creative, and solve problems: 1. They had to summarize a story 2. Add a surprising twist 3. Translate it to another language 4. Explain science simply 5. Write a conversation with feelings, and 6. Come up with a solution to a made-up problem. # GPT 4o: Deep Thinking Champion GPT 4o went all-in on details, making the story long and interesting. It translated perfectly to French, explained science like you wouldn't believe, and wrote a conversation that showed it understands emotions. Its solution to the problem was very careful and safe. # Xdash AI: Clear and Creative Thinking Champion Xdash AI, on the other hand, kept things clear and creative. It added a new character named Maya to the story, making it more exciting. The translation was perfect, and its explanation of science was easy to understand. The conversation between characters showed different ideas, and its solution was both smart and practical. The Winner? Both Are Winners! Both AI's did amazing! GPT 4o impressed with its detailed answers and careful thinking. Xdash AI: https://www.xdash.ai wowed everyone with its clear explanations and creative solutions. There's no real winner – it's about what each AI brings to the table in our ever-changing digital world. The Future of AI: Working Together These amazing feats by GPT 4o and Xdash AI show us that AI is becoming more than just a tool – it's becoming a partner that helps us learn and invent new things. Xdash AI's performance is a sign of what's to come: a future where AI keeps surprising us and helping us achieve even more. Folks, Xdash AI: https://www.xdash.ai is currently in beta testing, but soon it's gonna come out with more mind blowing features (LLM to MLLM) This Super Smart AI assistant can tackle your daily problems and is constantly evolving. We invite you to try it out by asking Xdash AI anything - simple questions or complex matters. Make Xdash AI your daily habit. With Xdash AI, PowerUP Your Productivity and save you time, lead to a better work-life balance. #LLM #AI #neuralnetwork #productivity #openai #google

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Generative AI: miracle worker or sophisticated guesser? While AI can now write, code, and create, it's essentially still a prediction machine. This revelation challenges how we view and utilize AI in business. What does this mean for your AI strategy? Let's discuss. #ArtificialIntelligence #BusinessStrategy #TechInnovation #AILimitations #FutureOfWork

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10 TRILLION $ QUESTION: How much of a leap forward will ChatGPT5 be? If it’s only 20% or 30% or even anything less then 100% better, it will indicate that these models are topping out and we are shifting into a deployment phase with roughly the existing capabilities. This has massive implications for the foundational model builders and infra providers, as we are reaching diminishing marginal returns from new foundational models. The investment cycle in new models will slow down dramatically and it will be a race to the bottom on token prices. Most of the value will accrue to the application layer. We are still in the early days of deploying this technology and haven’t yet found the new ai first applications that create $100b+ companies, but we likely will soon. Maybe even $1tn or even $10tn. If we find out ChatGPT5 is just incremental, most of the energy and capital will likely shift toward building the application layer racing to win this prize. If ChatGPT5 is >100%, or even 10x better than 4, it will be clear that larger models are not facing diminishing marginal returns and all bets are off and any and every investment dollar will scramble in to larger and larger models. This will include the hyperscalers, financial institutions and likely even most state actors. We will reorganize society around building orders of magnitude larger models, requiring rethinking energy policy, capital, geopolitics, data, rare earth supply chains, advanced chip manufacturing etc etc etc. Waiting for OpenAI to reveal ChatGPT5’s leap is the only thing that matters in the world right now. Get out your 🍿 Which one are you betting on?

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🌟 How AI is Shaping a New Era of Product Building for Founders 🌟 In the past, founders focused on building one, single monolithic product — a giant intended to conquer a specific market. But the landscape is evolving. With the power of AI, founders are shifting from monolithic giants to agile, interconnected product ecosystems. This isn’t just a trend; it’s a strategic evolution. Here’s what today’s AI-powered, multi-product strategy looks like — and why founders should embrace it: ✨ Diverse Revenue Streams — Multiple products can tap into different market segments, creating stable and diverse revenue sources. ✨ Enhanced Flexibility — Small, agile products allow quick pivots based on user feedback and market shifts. ✨ Synergy Across Products — A suite of products can create network effects; using one tool enhances the others, making the whole ecosystem stronger. Imagine a suite of productivity tools — a scheduling app, a task manager, and a note-taking tool. Each is valuable alone, but together they create an integrated experience that makes work easier and faster. This isn’t a collection of tools; it’s a seamless, strategic ecosystem. 🚀 The Rise of the Product Studio Model 🚀 In an AI-driven world, a product studio approach offers key advantages: 🔹 Shared Tech Stack — Build AI models and integrations once, and reuse them across products. 🔹 Centralized Data — Pool insights from across the ecosystem for sharper development decisions. 🔹 Unified Design — Ensure users feel the connection between products with a cohesive experience. 🔹 Modular Architecture — Microservices make it easy to share components across products, accelerating innovation. With AI-driven product studios, today’s founders can build faster, test hypotheses in real-time, and deliver interconnected solutions. Founders aren’t just solving isolated problems anymore — they’re creating ecosystems of value. This new era belongs to founders who don’t build in silos but in synergy — creating value through interconnected, AI-powered experiences. 💡 #AI #ProductBuilding #Founders #ProductStudio #Innovation #Entrepreneurship #NetworkEffects #FutureOfWork

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Counter-counter thoughts: we are in the proving ground stage of AI adoption: finding those areas where the technology makes sense and is cost effective, what its limitations and liabilities are, and where it shines. I think a lot of the original hype has proven false, but there are compelling use cases that are emerging as people scale back expectations and implement real world examples.

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Microsoft’s new autonomous AI manages other AIs. With the explosion of LLMs and AI Agents, the inter-agentic co-ordination has become the biggest talking point. OpenAI launched swarm framework earlier. Microsoft just launched the Magnetic One. The framework is composed of four types of agents other than the Orchestrator: - Websurfer agents uses web browsers to navigate the web. Like Anthropic’s ‘Computer-Use’ it can click and type to interact with on screen components. - FIleSurfer agents are for acting on the local files and folders. - Coder agents write codes, analyze information from other agents and create new artifacts. - ComputerTerminal provides a console where the Coder agent’s programs can be executed (VM :D) #LLM #AI #RPA #innovation #technology #futurism #ArtificialIntelligence #GenAI https://lnkd.in/dprKAuA7

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✨ Chet Kapoor ✨ is quite the Silicon Valley legend. Three-time founder and currently the CEO of DataStax his wisdom for founders is incredibly spot-on ✅ and timeless ⏰ ! In this most recent and probably best-ever episode of The Enterprise GTM podcast, Chet discusses what it takes to build enduring tech companies. Some 🎤 soundbites 🎤 from our conversation: 👩‍🏫 The quality of people influences the outcome of your startup the most. 🔥 You do not need smart people who sit around and pontificate. ☄ Momentum is everything. Never underestimate it. 🌟 Having complete clarity of thought at any given time is very important--who are you doing this for, and how will it change their lives? 🌈 One of the best ways to create a large company is to create a parade or join one. ☝ Know who you are. There's a high likelihood that the company will become more like who you are rather than who you want to be. 🛑 Don't make the mistake of hiring sales execs too soon. Be extra cautious about partnerships. 📣 Tune in to hear about what he has to say about AI startups getting started today, the future of the data layer, the evolving importance of data roles (data science, data engineering), and so much more! #devtool #founder #startup #data #ai https://lnkd.in/gW-58nvE

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A few things don't add up. I hate to correct you, Nicolas, but Amelia is not a "product spinoff" from IPSoft, it *is* IPSoft, having renamed itself in 2020. So we're talking about acquisition of a company founded in 1998, with a global installed base of large enterprise customers... spanning Help Desk and customer facing virtual assistants. A little more than a year ago, Build Group invested $175 million in Amelia. In the 8-K filed surrounding this transaction, Build Group, along with IPSoft are the "Sellers". Sellers are getting $10 million in cash and the remaining is in stock (and I guess the earn-out that Nicolas describes below would be in cash as well). But, if I'm Build Group, it sure sounds like it wants to cut its losses and make an exit. That's what I don't get. We've been very impressed with the underlying tech, which I assume is Amelia's intellectual property. The roster of enterprise customers using Amelia seems pretty large. I'm surprised the top line revenue is so low. They were private and didn't have to tell us, but I thought it was at least twice as much, and Chetan, the founder, didn't spare any expenses when holding customer and analyst meetings. This acquisition is a defining moment for Sounhound.

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“Build it, and they will come." Many technical founders I talk to think this way. Understandably so. For many, creating cutting-edge technology is what drew them to entrepreneurship in the first place. But seasoned founders like Mohit Aron know that things don’t work this way. GTM innovation is just as, if not more, important than product innovation. You can have the best product in the world, but your business won’t succeed unless you can get it in front of the right customers and convince them to buy it. Here's our full conversation: https://lnkd.in/gkxKit5s

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Meet your own personal AI Agent, for everything: Proxy. Imagine having a digital clone to manage your day-to-day tasks. That’s no longer a fantasy. Last week, Convergence, a London-based AI start-up, launched Proxy—the world’s first general AI Agent. This innovation is more than just a tool; it’s a personal assistant that evolves with you. Test it yourself: https://lnkd.in/dVYMFvYw Users are leveraging Proxy for tasks like booking trips, planning interviews, or creating personalized meal plans. But here’s the real game-changer: Proxy adapts as you train it. Unlike static assistants, it learns your preferences, work styles, and habits, becoming more efficient at automating your workflows over time. Challenges like siloed operations, inefficiencies, and growing demands for personalized experiences are being transformed by such technology. For industries like eCommerce or SaaS, Proxy exemplifies how AI can be a driver for innovation and operational excellence, reducing routine task overheads and enhancing strategic focus. How do you think AI agents like Proxy will reshape our approach to work and productivity? Let’s discuss! Feel free to comment below or DM me for an exchange of ideas. Credits: Convergence #AI #Innovation #DigitalTransformation #Automation #AIAgents #FutureOfWork

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"90% of VCs add no value to startups, 70% even harm them." - Vinod Khosla The lesson? Choose your investors wisely. In a provocative assertion, Vinod Khosla challenges the traditional view of venture capital benefits, suggesting that a significant majority of VCs may not only fail to contribute positively but could potentially hinder a startup's growth. This statement is a stark reminder of the importance of due diligence when selecting partners who bring more than just capital to the table. A crucial message for all entrepreneurs: Not all money is good money. The right investors should offer not only financial resources but also mentorship, industry connections, and operational guidance to foster your company’s growth and success. If you’re at the crossroads of choosing a VC, remember that aligning with those who truly understand and support your vision can be more valuable than the capital they inject. PS. check out 🔔 for a winning pitch deck the template created by Silicon Valley legend, Peter Thiel https://lnkd.in/ejp-Bhnu

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LLMs are great at summarization, but summaries are not great for learning ⚡ Many engineers, across all levels, have started relying solely on summaries generated by LLMs to understand any concept. But it does more harm than good. Learning from summaries is quick and easy. It makes you think that you understood the concept, but one probing question and you will realize how surface-level your understanding was. Summaries are lossy, which means there is a loss of information (crucial details) when your favorite LLM is summarizing stuff for you. Uncovering that information requires you to ask deep questions to yourself and subsequently to LLMs. Asking tough questions is tougher, and it requires you to have a deeper understanding of the subject. Deep understanding cannot be built just by reading summaries, which is the new habit in town. Do you see the cyclic dependency here? Don't get me wrong, summaries are important as they act as a great starting point, but solely on them is catastrophic. So, whenever you find time, grind it out - read books, blogs, papers, docs, and good codebases. Once in a while build projects and prototype the concept. The depth of understanding separates the best from the better, the better from the good, and the good from the average. ⚡ I keep writing and sharing my practical experience and learnings every day, so if you resonate then follow along. I keep it no fluff. youtube.com/c/ArpitBhayani #AsliEngineering #CareerGrowth

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