Jim Benedetto

Was chatting with another investor today on a call, and mentioned Tim Urban's Wait But Why Blog post, "The AI Revolution" and how prescient it was. Given that it was written in 2015, decided to flex AI's latest muscles to give it a new venue: a podcast. Podcast here: https://lnkd.in/gW8Dh89U Pretty easy to do: Step 1: Save the posts as PDFs. Step 2: Upload to NotebookLM, have it create a podcast. Step 3: Upload to Descript, give it captions. Step 4: Export, publish to Youtube. Total time to create the podcast: ~25 minutes. To generate this podcast and publish it even a few years ago would have taken >8 hours. Love the future (Original posts: https://lnkd.in/gW-PQXE7, https://lnkd.in/gg-nRvxz) #AIRevolution #GenerativeAI #WaitButWhy #TimUrban #NotebookLM #AIContentCreation #Podcasting #Descript #ArtificialIntelligence #ContentFlex #ProductivityHacks #FutureOfAI #AIinMinutes #TechEfficiency #AIandCreativity #YouTubePodcast #InnovationInContent #vibecap #vibecapital

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"Our goal is to create operating leverage through AI. ... One of the ways I look at it is, our total people costs will go down, our cost per head will go up, and my GPU per researcher will go up." — Satya Nadella. I finished listening to the BG2 podcast with the Microsoft CEO last night. Extremely interesting conversation with Brad Gerstner and Bill Gurley, and a lot to chew on. I found myself skipping back repeatedly to listen to certain parts again, to make sure I understood exactly what Satya was saying. One example was the quote above, in the context of the long-term implications of AI for the workforce, specifically at Microsoft in this case. I'd be very interested in hearing what everyone thinks of this. Here's that specific portion of the show: https://lnkd.in/gcPjHpeg Here's the full podcast: https://lnkd.in/gHAquZpD

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Get ready for the coming of the great wallet squeeze as AI-based tools and Agentic AI go after budgets. Kyle Poyar has an incredible post on substack that lays out the pricing model for AI-based tools. I'm quoting a sample but he has a mega list, below that you can scan... "The most disruptive AI pricing models so far ⤵ 1. Salesforce: $2 per conversation (Agentforce) 2. Intercom: $0.99 per AI resolution (FinAI agent) 3. Intercom: 10 free tickets per agent, per month (FinAI copilot) 4. Zendesk: Per successful autonomous resolution (Zendesk AI) 5. Microsoft: $4 per hour of usage (AI copilot for security) 6. OpenAI: Per input/output token (GPT-4o) 7. 11x: Per task completed by the AI SDR 8. Clay: Per credit with a credit = a data point or action 9. copy.ai: Per workflow credit 10. relay.app: Per workflow step" The net of it is that all these tools require wallet expansion. You still need your systems of record that you use today like CRM, ERP, HCM, etc. It's going to get messy and a lot of promising applications wont be able to bear the weight of their COGS in the face of fierce competition for static budgets. And don't underestimate the overlapping of AI add-ons when they come as discrete products. That is until we see the emergence of true Systems of Outcomes I recently wrote about where we have one application that does the work of systems of record and delivers an outcome. https://lnkd.in/g7tfrYgE

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Let me tell you what I really think. Subscription AI SaaS Sucks. The problem is not paying the subscription itself. It’s the whole circus that surrounds SaaS, with its interminable pre-sales, high-priced annual contracts, low adoption, and alarming churn rates. #enterprise #saas #ai https://lnkd.in/g9aepxi4

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Introducing Morfless, one of Antler's up-and-coming startup investments using AI to cut cloud costs. As cloud adoption continues to accelerate, so does the complexity and cost associated with managing cloud infrastructure. Morfless was founded by Ian Corbally and Domagoj Filipovic to address this issue head-on. The duo realised the pressing need for a platform that could automate the tedious tasks involved in managing cloud spend, thereby improving operational efficiency and reducing costs. Over the past 12 months, the startup has made significant strides, successfully developing and launching its AI-powered platform, gaining traction among a wide range of Australian and New Zealand sectors – from the largest national media websites to marketing agencies and software companies. Read more in Startup Daily here: https://lnkd.in/gHFjU_SM

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I'm really intrigued by this idea (not mine) that some bitcoin mining companies (Iris, Cleanspark, etc) have successfully built low-cost power shells that can now be leveraged by AI compute needs -- where power itself is becoming the gating factor in the continuing growth of AI. I think this will become a real 2025 story -- as the gating factor of "chip shortage" lessens, and the gating factor of "cheap power" rises in significance. There's not really a venture capital angle here, but there is a public market one. Perhaps more importantly, it becomes a touchpoint between "crypto" and AI. Something to ponder and keep an eye on (full disc: I own a bunch of bitcoin miner stocks, including those mentioned above).

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Sweetndata, a South Korean AI-based fandom content startup, secured CNTTech funding to enhance AI fan cards, advance global expansion, and broaden its platform to diverse markets.

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AI memory is fundamental for conversational AI and AI agents. It is critical for building personalized experiences and improving reasoning. Check out Letta’s course to understand how to use AI memory to enhance the customization and quality of your AI app.

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➰ APIContext's latest insights on cloud-based API performance have been featured on Nordic APIs! In the 2024 report, we delve into crucial aspects affecting API efficiency: 🔐 Authentication is key. Ensuring robust authentication mechanisms in APIs is crucial, yet offloading this function can introduce complex challenges. 📖 DNS configurations matter. How you handle DNS settings can significantly impact API performance, particularly when tied to authentication processes. 🌐 The role of third parties. Critical third-party services play a significant role in 🔗 API transactions, underscoring the need for careful integration and monitoring. ⛅ Not all clouds are created equal. Differences in cloud services can drastically affect API performance, an essential consideration as APIs account for over 80% of all internet traffic. #APIs #CloudComputing #TechInsights #APIContext

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Many assumed that the industry would be well on its way to AGI or superintelligence before AI model builders’ efforts to take advantage of scaling laws might hit a wall. Recent headlines are chipping away at that assumption. One question I've been getting in my inbox: is this the era of diminishing returns for AI? We don't think so. Even if an avalanche of new clusters and synthetic data fail to deliver significantly better model performance, there are good reasons to believe that AI is still going to become orders of magnitude more powerful in the coming years — powering a new generation of startups and ultimately productivity growth and positive benefits for mankind. In fact, with agents and reasoning just beginning to scale and thousands of industry-specific models coming online, it's about to get really exciting. Read our latest blog post on the topic: https://lnkd.in/gFhniNX8

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PSA: Stop using the original OpenAI CLIP weights. I see a lot of people using CLIP for multi-modal retrieval. What many people may not know is that there are 100’s of CLIP models now since OpenAI’s original release. These newer models offer significantly better performance across many benchmarks. For product search related tasks we recommend the following. + Fastest inference: ViT-B-32 [laion2b_s34b_b79k] + Best balanced: ViT-L-14 [laion2b_s32b_b82k] + Best-all round: xlm-roberta-large-ViT-H-14 [frozen_laion5b_s13b_b90k] You might notice these are not the ones that perform the best on the benchmarks. Why? Because the benchmark only test for very specific tasks which are often quite different from search and recommendations. These are ones we have found to be the best for product related search and retrieval tasks and generally very good first choices if you are unsure where to start (even for non-product related search). Here is a hugging face space with all the data: https://lnkd.in/gxu5UYkt Read more: https://lnkd.in/g5_D4ccs

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Kim Burgaard Rachel Perez Jay Leverett David Bellotti -- I'll be listening to this one for sure! Sergio H. Serge Madenian Episode Summary: The episode features an in-depth interview with Mike Krieger, the new chief product officer at AI company Anthropic, discussing his background, the decision to join Anthropic, the company's focus on responsible AI development, the challenges and opportunities in building AI products, and his vision for the future of AI technology and its applications. https://lnkd.in/guWW8cku

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Congrats to Vultr on raising $333M from AMD and LuminArx Capital, achieving a $3.5B valuation. Impressively, this is Vultr’s first-ever capital raise, having been fully bootstrapped and funded by operating cash flows. It’s a great example of a disciplined growth strategy, which minimizes dilution and compounds equity returns — nail the business model, prove out ability to scale with attractive unit economics, and THEN (perhaps) use outside capital to accelerate growth. #AI #Cloud #CapitalMarkets #VC

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I like this idea of "technical taste". It gets into where software engineering is as much creative art as it is science. Four great takeaways (IMHO) for software devs in this era in particular: 1. Aspiring engineers should cultivate a sense of curiosity, experiment with different tools and technologies, and embrace a mindset of continuous learning. 2. AI has the potential to streamline processes and enhance productivity for engineers, but it may also lead to disruptions in traditional software development workflows. 3. Developing technical taste and judgment is essential for making informed decisions about which technologies and approaches to pursue. 4. Collaboration and open-mindedness are key to leveraging the full potential of AI and staying ahead of technological advancements. I also really liked these two quotes from Sam Schillace: 1. "The right time to do something is when you have that feeling in the pit of your stomach that's like, 'oh, this is a great idea and it's going to suck to build because nothing's ready yet.'" 2. "Technical taste is like, 'how well have you consolidated that set of experiences and heuristics into judgment that you can apply accurately when you see new things?'" 3. "It may be the case that very small teams can do very large projects, or like we were talking about before, it may be the case we're just going to get really ambitious about what we try to do with the same size of teams, which is kind of where I would put my money." Great job on continuing to put out great episodes, Brett Berson and team First Round Capital! #ai #engineering #softwaredevelopment

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New Metrics Utilizing Universal Laws: Power Law https://lnkd.in/gvzr3Htx

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Anyone have an idea as to when Google will open up AudioLM or Soundstream via API? Seems like they could take a huge chunk of the speech synthesis market if they wanted to, as their current TTS models lag way behind in quality compared to offerings from startups. Generative speech and audio are interesting modalities in that “smaller” startups (like 10-100M funding) are at the vanguard instead of the large incumbents. I guess this correlates to potential market size of the modality? Or maybe correlated to risk? Generative audio is perhaps riskier than text, like can be used for more nefarious purposes?

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The predictable enshitification of maps with ads: https://lnkd.in/g8ptc4_s But hey, what if it was all more contextually relevant? Like what if you really needed gas and it showed you gas stations nearby? Isn't that useful? That's still a very likely "no" -- esp. if the ad-tech company is using your personal information against your personal best interests. E.g., even if you do need gas, the system can hurt you if the ad auction winner is more expensive, got worse reviews, and was farther out of your way than the other options you weren't told about. FWIW, at Keyhole (which became Google Earth after acquisition) we also played with how to monetize maps via ads. Serving earth data is very expensive, esp. for a small company without cloud resources. The best idea we had was to promote map labels to show up earlier or more prominently when zooming or panning in, based on a prior auction. Turns out, you never want to show all possible map labels at once -- TMI. Highlighting a key city name often leverages negative space (no labels) around it. So the ad auction would be one way to pick and prioritize which comes first to make everything more readable. Contextual picking is even better. We also played with less conspicuous visual ads. But none of these were very satisfying. All felt kind of icky, so we never did it. Google won our attention in the 2000s not simply because search worked better than the other options, but because the text ads were small and easy to ignore. Remember that? Ad-tech business models always drive to the worst outcome over time.

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