Konrad Feldman

Here are some early insights from the survey we are using to inform our Sept. 19 roundtable on generative AI monetization. Michael Mansard, Kyle Poyar and Steven Forth will go deep into the trends in generative AI and how it us being monetized. We include lists, categorized by AI, on what people worry about with generative AI and what gets them excited. https://lnkd.in/gNXDt8Ry #SaaS #pricing #monetization #AI #genAI #generativeAI

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Today, GTMfund’s is excited to announce to launch of Operator, its first incubated company. Max Altschuler (founder of GTMfund) teamed up with co-founder Adam M. (design engineer and 0-1 builder) and co-founder Mark Kosoglow (Outreach employee #1 and former SVP of Global Sales) to create Operator.ai alongside an insanely talented team Pleasant Middelhof, Jeremy Jonas, Carl Gunderson. We've entered a period called “The Great Ignore”. Spam and irrelevant, poorly-automated outbound campaigns are running rampant.   Operator gives you an easy-to-use Growth Engineer that allows you to build and enrich lists with accurate data, and run experiments and queries using AI to generate highly targeted outreach.    Check out their website to get updates, early access, and see how they are taking the world back to 2 touches meant to attract buyers into conversations that convert, instead of 20 touches meant to make sure you hit your activity number: https://www.operator.ai/

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Big announcement below! 👇 Let's talk about the current state of GP-LP affairs: 🤯Emerging VC managers have absolutely exploded over the past 5 years. 📈 At the same time, more and more data has surfaced that shows that emerging VC firms tend to outperform larger, established firms. 🤔 All of this has made it intriguing but tough for LPs to know where to direct their attention. 🛍 GPs frequently meet LPs at conferences who are window shopping but not committed to the asset class or emerging managers. 🧾 And both crews get overwhelmed by transactional convos. So Sydney Paige Thomas and I created Abundance. Abundance is a private, nomination-based retreat for active LPs and top emerging GPs to form new experiences together and build lasting relationships. Why Abundance? Abundance is knowing that there is more than enough for more than one to succeed. And a single win within a community is a win for the community itself. The journey of an emerging VC manager from 1st close to final close or Fund 1 to Fund 2 is (1) communal and (2) requires an abundant mindset. LPs look for structure and confidence to feel comfortable investing in early VC firms. Yet many of the feeds we scroll and conferences we attend reinforce inherent power dynamics and transactional thinking, which allows scarcity mindset to creep in for emerging GPs. Some of the best events I’ve attended have been intentionally non-transactional, e.g. Camp Hustle, Recast Summit, and other GPs’ AGMs. The fundraising success stories we see usually involve a community (usually of other GPs & LPs) coming together to support and open doors for the emerging GP. We designed Abundance to be an immersive gathering that fosters these connections. Starting tonight, ~100 GPs and LPs are descending upon Seattle for the inaugural Abundance retreat. This has been under wraps for months and I can’t wait to see it come to life! Thanks in advance to our awesome sponsors who were the earliest believers in this vision: Sydecar, Amazon Web Services (AWS), Gunderson Dettmer, & Zelda Ventures. And shoutout to my dad Ed Illig for logo design & Halle Kaplan-Allen being the first sponsor to say yes 🤩 Presented by The Council Capital & Symphonic Capital.

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Daniel Wilson and Reza Rassool Thanks for the opportunity to join the conversation, and more importantly to contribute to the critical work of Kwaai Personal AI -- turning AI into a meaningful benefit versus a threat in people's lives. (My comments start about 30 min in, after Reza's introduction to Kwaai))

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Hey folks, I think you might be aware that what we're building at DeepCast includes a podcast discovery and exploration platform for listeners at www.deepcast.fm. We also recently unveiled www.deepcast.pro -- a promotions, marketing, and monetization platform for podcasters (and folks like networks and agencies who support them). "You make the shows, let us help you with what comes after." Shows claimed and processed via DeepCast Pro are also published for listener consumption on DeepCast. High value all around! If you're a podcaster, claim your show at www.deepcast.pro to get started. Free speaker-labeled transcripts for all your episodes as well as generated insights for each (key takeaways, quotes, topic & keyword sets, summaries, and more) plus many more features—and growing daily! We're shipping fast over here! (Thanks to Rachel Perez Hosna Qasmei Kim Burgaard Benjamin Moon Rachel Magana Hari Ramachandran!)

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https://lnkd.in/ecuZDqKz. https://lnkd.in/ecuZDqKz Liquid AI Introduces New Class of Foundational Models, Advancing AI Performance and Efficiency Boston, September 30, 2024—Liquid AI, a pioneer in artificial intelligence innovation, is set to redefine the AI landscape with the launch of its Liquid Foundational Models (LFMs). These models bring unprecedented levels of performance and efficiency to generative AI, offering powerful solutions for industries looking to harness artificial intelligence more effectively on device or on server. A technical whitepaper about model performance will be available on September 30, 2024, at 11 am EST. Key Highlights: ● LFMs Introduce a New Scaling Law for Generative AI: Markedly improving quality, cost-effectiveness, and power efficiency compared to current GPT models. ● Innovative Architecture: Leveraging dynamical systems and advanced mathematics, LFMs achieve superior performance with fewer parameters. ● Initial Model Release: The lineup includes models with 1B, 3B, and 40B parameters, each setting new benchmarks in their respective categories. ○ LFM-1B: A 1.3-billion-parameter model achieving the highest scores across benchmarks in its class. ○ LFM-3B: A 3.1-billion-parameter model that outperforms many 7B and 13B models, making it ideal for edge deployment and resource-constrained environments. ○ LFM-40B: A 40.3-billion-parameter Mixture of Experts (MoE) model designed for complex tasks, offering performance comparable to much larger models while remaining cost-effective. Real-World Applications: • Enterprise: LFMs enable the design of more powerful AI assistants and analytics tools that can run efficiently on existing infrastructure, reducing operational costs. • On-Device: LFMs prioritize privacy, low latency, security and offline accessibility, making them suitable for mobile and edge deployments. These models have demonstrated impressive results on standard LLM evaluation benchmarks. Additionally, LFMs maintain near-constant inference time and memory complexity, allowing for longer input sequences without significant increases in computational resources. Advancements in AI Architecture: LFMs introduce a new design space for foundational models by employing adaptive linear operators rooted in dynamical systems and signal processing. This approach unifies and extends existing computational methods in deep learning, providing a systematic way to explore architectural possibilities. The models are highly adaptable, optimized for various hardware platforms including NVIDIA, AMD, Qualcomm, Cerebras, and Apple devices.

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