Shawn Chauhan’s Post

AI agents are an advanced evolution of current large language models that are designed to process information and execute tasks without human intervention. They do more than simply answer questions and summarize documents like chatbots but also integrate tool-using capabilities so that they can operate autonomously using human-like reasoning to make decisions. For example, they can send emails, write and send tweets, prepare and send reports based on events and more. #AIAgents https://lnkd.in/gU8jZsjq

“Don’t Wait on AI”   This insightful article in Inc. Magazine features Sam Altman's interesting advice to entrepreneurs… "Don't Wait on AI".   His advice parallels the platform shifts on both Mobile and the Internet (unless you build for both, your venture is unlikely to get very far).   This advice also reminded me of the opening paragraphs of a book which I recently read, “Power and Prediction – the Disruptive Economics of AI”. It’s a great read, and among other things, it illustrates how the evolution of electricity required a combination of Point Solutions, Application Solutions, and System Solutions, to finally achieve critical mass.   I believe that Generative AI will likely go through the same evolution.   Here are some examples:   Point Solutions - They are specific, standalone innovations that address individual problems. An example with Generative AI could be a model which creates realistic images from textual descriptions. While somewhat impactful… its impact is limited without broader integration. Think JARVIS from Iron Man.   Application Solutions - These solutions typically involve integrating multiple Point Solutions into a larger solution. As an example with Generative AI, this might mean combining multiple text-to-image models along with natural language processing (NLP), in order to create virtual assistants that can generate content, answer questions, and/or engage in more dynamic conversations. Think of the movie, HER.   System Solutions - They involve a larger ecosystem of Point Solutions and Application Solutions. For Generative AI, this includes the development of interconnected AI systems in larger ecosystems. Think of Tom Cruise entering the mall in Minority Report.   I think AI’s transformative ability may hinge on its integration with these different levels of solutions.   As #entrepreneurs, we have the opportunity to explore and implement #AI across all three of these solution layers to drive innovation.   What do you think?   Do you believe that Generative AI will go through the same evolution, or that it will evolve in a different fashion?   Let me know in the Comments section below! #entrepreneurship #generativeai #wednesdaywidsom

👋 Can anyone keep up with the dizzying pace of AI advancements? 🚀 1. OPENAI ON ANOTHER LEVEL 🔝 OpenAI has just announced its new reasoning model, o3. This one outperforms leading AI technologies in math, science, coding, and logic. What’s the big deal? 👉 This model pauses, thinks, and explains its reasoning before answering. 👉 It’s trained to tackle complex tasks like never before. 👉 OpenAI is pushing the boundaries. But how do we, as women entrepreneurs, leverage this new tech? 💡 PROVOCATIVE INSIGHT: Is this going to create a new divide? Will only the big players thrive while we small startups struggle in the shadows of these tech giants? How can we harness o3 without drowning in its capabilities? 2. AI-RACE HEATS UP WITH GOOGLE 🌡️ Google recently unveiled its Gemini 2.0 Flash Thinking. Sounds fancy, right? 👉 Both Google and OpenAI are racing to deliver better-meaning AI that can solve tougher problems. 👉 They are not just improving algorithms—they’re changing the game altogether. 👉 But let’s face it, who really benefits from this? 😰 REAL TALK: As smaller entities in this rapid competition, can we keep pace? Or do we risk being overshadowed by these massive corporations? Is it wise to dive into the AI sector now, or should we wait till it stabilizes? 3. NVIDIA'S NEW AI SUPERCOMPUTER 💻 NVIDIA just rolled out the Jetson Orin Nano Super, touted as the most affordable generative AI supercomputer. What does this mean for women-led startups? 👉 Prices dropped, making AI tools more accessible for all. 👉 A boost in generative AI inference performance, up 70%, means faster and smarter applications. 👉 The accessibility game has shifted, but can we compete in a more crowded field? 💬 THE REAL QUESTION: With advanced tools in everyone's hands, does our value come from technology or creativity? How do we maintain a competitive edge when the barriers to entry fall? 🔮 WHAT’S NEXT? AI is evolving rapidly, and we must stay adaptable. As women entrepreneurs, we can thrive by leveraging these advancements smartly. Are we ready to seize these opportunities? Share your thoughts and strategies below! 👇 🫡 𝐁𝐮𝐢𝐥𝐝 𝐲𝐨𝐮𝐫 𝐬𝐭𝐚𝐫𝐭𝐮𝐩 𝐧𝐨𝐰: https://femaleswitch.app 🔈🔈🔈 🫵 𝐅𝐨𝐫 𝐬𝐭𝐚𝐫𝐭𝐮𝐩 𝐚𝐝𝐯𝐢𝐜𝐞 𝐟𝐨𝐫 𝐟𝐢𝐫𝐬𝐭 𝐭𝐢𝐦𝐞 𝐞𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫𝐬, 𝐡𝐢𝐭 𝐅𝐎𝐋𝐋𝐎𝐖 #startups #femalentrepreneur #zerocode #ai

We've seen lots of mega raises this year that are capitalizing the appetite for AI innovations. Here's a good report from Pitchbook that gives more color. #ai #aideals #vc #venturecapital #machinelearning #llm #NLP

his was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources. Amidst the recent expansion of artificial intelligence (AI), we’ve visualized data from Quid (accessed via Stanford’s 2024 AI Index Report) to highlight the top 15 countries which have seen the most AI startup activity over the past decade. The figures in this graphic represent the number of newly funded AI startups within that country, in the time period of 2013 to 2023. Only companies that received over $1.5 million in private investment were considered.

As someone who's been keeping a close eye on the startup scene for years, I've gotta say, AI is really shaking things up. These AI-driven startups are popping up left and right, and they're using cutting-edge tech like machine learning and natural language processing to create some seriously cool products and services. One of the best things about AI is that it's becoming more and more accessible. You don't need a PhD or a ton of cash to get started anymore. With open-source libraries and cloud platforms, even small startups can harness the power of AI to innovate and grow. Investors are taking notice, too. According to Crunchbase AI startups raised around $20 billion in FEBRUARY. That's a lot of faith in the potential of AI to drive serious value. But it's not all sunshine and rainbows. As AI gets smarter and more autonomous, we've got to think about the ethical implications. Bias, privacy, and unintended consequences are all real concerns that startups need to address head-on. (As well as English language hegemony!) Now, I know what you might be thinking - Bizblip doesn't look like a tech company, so what does this have to do with us? Here's the thing: we've been using readily available AI products to streamline our news production, and it's been a game-changer. We've cut costs by a staggering 90 percent, all while maintaining the quality our readers expect. I'm putting together a pitch deck right now, and that's not even something I'm mentioning... because I think EVERYONE should be doing this! How are you incorporating AI into your business? Especially if you're NOT an AI company?

Perplexity, a two-year-old San Francisco startup that has built an AI-powered search engine and answer engine using natural language processing, closed a $500 million round at a $9 billion post-money valuation, an amount that is 3X its last valuation in June. IVP was the deal lead. https://lnkd.in/gkNmEs5S

Is OpenAI upending the famed VC model of Silicon Valley? An interesting take on valuations, the exponentially increasing funding that ever larger #LLM require, and the doubts about the ability to for monetization. The Economist #AI #VentureCapital #GenerativeAI https://lnkd.in/dxxCuxsz

It’s the new blueprint for Big Tech companies scrambling for dominance in artificial intelligence: Hire the cofounders of a high-profile AI startup along with some of its staff. The latest example came when Google said the cofounders of AI chatbot startup Character AI and some members of its research team would join its already substantial AI efforts. The announcement is a lot like what Microsoft did in March when it hired a big part of the workforce at AI startup Inflection, including CEO Mustafa Suleyman, and what Amazon did in June with AI company Adept. If three is a trend, there is clearly something trendy happening in the world of AI startups—and it may not be these deals to absorb AI upstarts without actually buying them. Instead, it may be that the AI startup era itself, which has soared wildly for over two years, is beginning to implode. Read more: https://lnkd.in/eN_48E8c

"Deepseek is AI's Sputnik moment", declared the venture capitalist Marc Andreessen. But, for those who are intimate with the subject, and not in the business of hyping up the technology to raise funds, the writing on the wall was that the comings of such new kids on the block, albeit not at such breakneck speed and performance. I certainly didn't see it coming. DeepSeek coming out of China also made the wave even more amplified although it should have made perfect sense as China and India produce the largest number of STEM graduates globally. Recently, I interjected in a discussion between Joseph Kibur and Mikael Alemu Gorsky regarding the use of AI to support a solo business/enterpreneurship, where I made a slight quip on Generative AI, and its hyped dominant subset LLMs. Both Joseph and Mikael are consummate professionals and enterpreneurs - and they have my ears and I also regularly read their interesting feeds. My honest view was to piont out that AI is still not mature enough to replace those (legally) loyal, creative and passionate employees that use reasoning to make a start up succed. On the subject of AI, I agree, Deep Learning (the primary route taken by Open AI) really works but Deep Reinforcement Learning (the primary route taken by Google DeepMind) works even more. So does DeepSeek-R1 that was released on 20th January, and what is more, it is opensource. What makes DeepSeek and its performance great is that it is largely based on reasoning algorithms similar to those of DeepMind although it is shown to outperform current AI tools available to the public and businesses. Notwithstanding, my money is still on Demis Hassabis's DeepMind. Not only they are doing great things for humanity on contributions like AlphaFold but their ethos is to understand and mimic intelligence itself. OpenAI's ethos is marketed widely but not succintly and I will struggle to describe it except saying they prioritise equitable AI development. Despite originating from an authoritarian state, DeepSeek is opensource, which "may" make the AI game field much more interesting than it has ever been. Caution is in order here. Does DeepSeek chose the open-sourcing route both to attract attention to their supreme capabilities and collaborate with the international AI ecosystem and then close it later either for business or geopolitical reasons? Let's wait and see but the game seems really on. The current performance metrics must be chosen judiciously and the jury is still out there if cost of development and speed up alone warrant a winner as we are still few years away from Artificial General Intelligence (AGI), which is the Holy Grail. Is the substrate for AGI will remain the scaffoldings of big power hungry GPU type data centres that lack latency or the innovative edge-AI solutions powered by efficient FPGAs that are locally deployed on organised and high value data, only utilising the cloud as their public libraries? We shall see NEXT TIME.