Xuhui Shao

17-year-old Eric Zhu built Aviato, an analytical platform for private market data, in his high school bathroom. Now, Aviato has emerged from stealth with $2.3M in venture #funding. The platform tracks various metrics like funding rounds, headcount, and #employee vesting schedules, aiming to add an analytical layer missing from competitors like Crunchbase and PitchBook. Zhu’s interest in #startups began during the pandemic through Discord group chats. Previously, he launched and sold Esocial, a digital platform for schools. Aviato has secured clients like NEA, Republic Capital, and 8VC. Zhu has moved to San Francisco to expand Aviato and finish his high school degree online. #Startup #Entrepreneurship #Innovation #DigitalMarketing #TechTrends  #AI #VentureCapital #Ecommerce #Leadership #BusinessGrowth Discover this innovative startup at The Founders. Subscribe and support. https://lnkd.in/gPiktEDK If you spot any inaccuracies, please let us know so we can correct them. Your feedback helps us improve. Thanks! 

18

3 Comments

What do you do when a radical new technology puts your main product right in the crosshairs of disruption? Listen to David Okuniev — co-founder of Typeform | Ask awesomely — discuss the challenges of innovation within existing structures. David shared a game-changing insight: Radical innovation is really, really difficult to do inside your own product. He emphasized the need to break free from the constraints of familiarity and embrace change from outside the box. Henrik Werdelin and I have both seen our fair share of this in our respective careers. What struck us most was how David leveraged structure to overcome the innovator’s dilemma. By creating a culture of experimentation and providing space for bold ideas, he propelled Typeform beyond incremental improvements. What other hacks have you seen or employed to help your organization overcome the innovator’s dilemma? Share your stories below! 👇 And if you want to dive deeper into our conversation, click the link in the comments to catch the full podcast episode!

4

2 Comments

Sharing a sanitized version of the mu ventures Q2 q'ly LP update. Included musings: 👉 SEOs shrinking impact, and the rise of LLMO (large language model optimization) 👉 examples of the Commerce AI application layer coming to life 👉 a modern fund strategy that accepts companies require less capital, time, and people to trigger the power law 👉 Mu's guide to investing in AI 👉 all 30 companies in the Mu-niverse (and several others we admire) Founders, VCs, LPs - if you like how we think and suspect we can partner, hit us up! https://lnkd.in/dTJ2zjav

49

5 Comments

Introducing the Alinia AI Alignment Platform. From their announcement: "Alinia AI enables companies to evaluate the performance of their GenAI applications and obtain evidence on how aligned these are to their values, policies, and business preferences. Following the performance assessment, Alinia AI recommends the best next actions to further guide and control LLM output and improve alignment."

10

5 Comments

Founderville believes one of the most significant opportunities is emerging in legacy system applications. We look for manual tasks to leverage AI for efficient automation. Rather than chasing massive TAM, which will be addressed by larger VCs, we focus on smaller market domains that won't be chased as hard. Think of "boring" processes that require human intervention or manualized tasks. Those are opportunities. Keep your eyes open if you have deep domain expertise in a non-automated and fragmented industry. #entrepreneurs #venturecapital #startups #saas

17

7 Comments

💡 Why do we need so many evaluation tools for LLMs? As engineers, we build 'production-ready' LLM products using these metrics. But what happens next? How do we maintain control and ensure reliability? At Feedback Intelligence, we’ve crafted a cookbook to keep your LLMs reliable and aligned with user expectations. 🍲 📖 Give it a read and let’s chat!

16

DePIN & RWAs dominance isn't as far off as most people think. Across every innovative cycle, three fundamental pillars emerge: foundational technology development, proliferation of infrastructure, and a surge in application development. As we venture into the third cycle, DePIN and RWA protocols are poised to become market leaders paralleling the dominance witnessed by infrastructure projects from 2015 to 2024.

28

2 Comments

Here are the Top 10 SaaS funding rounds of the past week (Seed to A) Starting at number 1... 🥇 Emergence, $97.2mm Seed 🤯 Emergence is developing an AI "agent-based" system that automates tasks typically performed by knowledge workers. Founded by Satya Nitta. 💸 Investors: Learn 🔗 https://bit.ly/3XSitTA 🟠🟠🟠 🥈 Formic, $27.4mm Series A Formic enables manufacturers to scale faster by making it easy to deploy robotic automations, like packing and palletizing. Founded by Misa Ilkhechi and Saman Farid. 💸 Investors: Blackhorn Ventures, FJ Labs, and more 🔗 https://bit.ly/3XGzEYr 🟠🟠🟠 🥉 normai, $27mm Series A Norm Ai is automating compliance processes, making them more efficient, cost-effective, and accurate via (you guessed it) AI. Founded by John Nay. 💸 Investors: Coatue, Bain Capital Ventures, and more 🔗 https://bit.ly/4ckpNft 🟠🟠🟠 🎖️ 4. ORA, $20mm Series A Ora is a blockchain project incorporating AI into dapps. Founded by Kartin Wong. 💸 Investors: Polychain Labs, HF0, and more 🔗 https://bit.ly/3zpW7Ph 🟠🟠🟠 🎖️ 5. Payabli, $20mm Series A Payabli builds the infrastructure that allows companies, specifically software companies, to embed and facilitate payments through APIs. Founded by Joseph Elias Phillips and William Corbera. 💸 Investors: QED Investors, Bling Capital, and more 🔗 https://bit.ly/4bwkGHE 🟠🟠🟠 🎖️ 6. Sift, $17.5mm Series A Sift develops tools to accelerate the development and ensure the reliability of complex machines (think Spacecrafts). Founded by Austin Spiegel and Karthik Gollapudi. 💸 Investors: GV (Google Ventures) 🔗 https://bit.ly/3L7zlyk 🟠🟠🟠 🎖️ 7. Ario, $16mm Seed Ario is an AI-powered assistant for parents that helps with daily tasks, from meal planning to scheduling playdates. Founded by Sumit Agarwal. 💸 Investors: Wing Venture Capital, Floodgate, and more 🔗 https://bit.ly/4eEjeG9 🟠🟠🟠 🎖️ 8. MagicSchool AI, $15mm Series A MagicSchool provides lesson-planning solutions for teachers to fight burnout. Founded by Adeel Khan. 💸 Investors: Bain Capital Ventures, Adobe Ventures and more 🔗 https://bit.ly/3RQt5Pn 🟠🟠🟠 🎖️ 9. AuthZed, $12mm Series A Authzed makes it easier for developers to build permissions in their applications. Founded by Jacob Moshenko and Jimmy Zelinskie. 💸 Investors: General Catalyst, Work-Bench, and more 🔗 https://bit.ly/4bqkh9B 🟠🟠🟠 🎖️ 10. SLUSHY.com, $10.2mm Seed SLUSHY is a creator monetization platform. Founded by David Gross and Fred Sprivock. 💸 Investors: Mantis Venture Capital, Jon Oringer, and more 🔗 https://bit.ly/4eN9Boi ⚫⚫⚫ I'm Gyan, Head of Community at Venture House. I create tools, guides, and other free resources for Junior VCs and founders. If you found this helpful, check out the Venture House website for more 👇 https://venturehouse.xyz/ #startups #venturecapital #funding #saas

40

1 Comment

"Editors note: Welcome to issue #2 of Transcriptions. Today, we’d like to present a conversation between Qasar Younis of Applied Intuition, and Bilal Zuberi of Lux Capital. We discovered Qasar recently, and find his focus and clarity of thinking to be admirable. What follows is a lightly edited transcript of their talk, first held at the Paklaunch forum." Link to transcipt: https://lnkd.in/gH4uBmPE

12

2 Comments

Friends, Q2 was a quarter of progress and learning for us at HawkTower, where we invest in early-stage startups applying breakthrough computing technologies to maximize California's natural resource markets. Our focus is on technology-enabled interventions (e.g., AI-enabled geospatial radars for lithium-ion batteries in the waste stream) for critical, market-level imperatives (e.g., disaster prevention) that can drive rapid commercial adoption (e.g., placed on every recycling truck in the world). Our current investment priorities are: - Agricultural productivity and efficiency - Biomanufacturing - Labor and mobility automation - Waste stream optimization and decarbonization - Disaster prevention and management Here’s a snapshot of what we’ve been up to: Milestones and Investments: - In late April, we officially launched our fund, filing with the SEC. Yay. - By June, we completed our first fund close ahead of schedule, with backing from family offices, foundations, high-net-worth individuals, and organizations aligned with California's future. - Our portfolio now includes three early-stage investments (Farm-ng, Agriful Software, and Nexstera Tech). Strategic Partnerships: - We believe that startups operating closer to their customers and resources, especially in agriculture and biomanufacturing, have a strategic advantage. For instance, the Salinas Valley, a major agricultural hub, is less than an hour from Silicon Valley and serves as a center of thought leadership in the convergence of agriculture and AI (from Western Growers, Taylor Farms, and others). - Similarly, the North San Joaquin Valley is emerging as a biotech and agtech innovation hub, and we are proud to support BEAM Circular, a startup hub for the circular bioeconomy. Key Relationships: - Karen Warner, CEO of BEAM Circular, joined HawkTower as a strategic advisor. - Jackie Cruz, Ed. D. Cruz, Hartnell College’s VP of Advancement, advises on Salinas Valley and workforce development. - Ben Palone from Western Growers, with his technical background in agriculture, became a trusted advisor. - Matthew Hoffman from Driscoll's Global R&D team provides insights on global agriculture, product positioning, and investment strategy. - We collaborated with Monterey Bay DART for workforce development and automation in agtech. - Dominic Milano and the Milano Technical Group from Merced collaborated on key initiatives and advised us on investments. - HawkTower is participating in Santa Cruz Works's accelerator cohort as a mentor and advisor. Thank you Doug Erickson. - We published an overview of entrepreneurship across the UC system with input from across the University of California system. Moving into the fall, we remain deeply committed to supporting founders shaping California's future natural resource markets. Stay tuned and be in touch! : ) Db

87

5 Comments

RLHF is a traditional and well-known technique that helps practitioners to correct ML/DL over time. With the rise of LLMs, it's essential to have a proper RLHF as LLMs are non-trivial by nature. Right now, only foundation model companies and big tech can afford it in its current form at scale as it is complex and costly. Additionally, the collection of human feedback is usually done via a very simple mechanism: they are prompted to choose from two options of generations for each given prompt. This aims to reduce the labeling costs but provides a weak learning signal for the reward model that will be trained on this data. Finally, evaluators do not have sufficient context of the task and that’s the reason they introduce bias. We introduce an alternative to RLHF that optimizes LLMs through 'personalized' feedback. Read why RLHF matters in the context of LLMs and more here: https://rb.gy/1xcx05 #llms #rlhf #feedbackintelligence

43

4 Comments

What I appreciate most about how we designed the SMArtX Advisory Solutions platform is that we provide software to Turnkey Asset Management Programs as a FinTech, but we prove out every piece of our technology platform by using it to run a TAMP and servicing advisors ourselves. In tech this is called "Eating your own dogfood" or simply "dogfooding". Wikipedia says: "Eating your own dog food or "dogfooding" is the practice of using one's own products or services. Hence dogfooding can act as quality control, and eventually a kind of testimonial advertising. Once in the market, dogfooding can demonstrate developers' confidence in their own products." No matter how you cut it, whether we are servicing them directly or through our enterprise clients; the end consumer is the advisor. And servicing them through an "out-of-the-box" TAMP gives us the unique opportunity to hear the clients needs directly and hone our product and make it a better experience for everyone using it. So let's be both a TAMP and a FinTech while we sing along with Dierks Bentley and agree that SMArtX is "little bit of holy water, but still a little bit burning man"

11

Andrej Karpathy is about to release a new LLM course, (Karpathy was the director of AI @ Tesla & early Openai employee.) In my opinion he is the best teacher on AI/ML topics, better than Andrew Ng. Here is his Youtube channel: https://lnkd.in/gUaNzvXe With this video being a personal favourite: https://lnkd.in/gjiCKwJm "Let's build GPT: from scratch, in code, spelled out." Another of his repos creating a LLM in c that can run on a mobile phone. https://lnkd.in/gjbqwQ24 This new course is not released yet, but you should bookmark it https://lnkd.in/g3Emytgs Syllabus Chapter 01 Bigram Language Model (language modeling) Chapter 02 Micrograd (machine learning, backpropagation) Chapter 03 N-gram model (multi-layer perceptron, matmul, gelu) Chapter 04 Attention (attention, softmax, positional encoder) Chapter 05 Transformer (transformer, residual, layernorm, GPT-2) Chapter 06 Tokenization (minBPE, byte pair encoding) Chapter 07 Optimization (initialization, optimization, AdamW) Chapter 08 Need for Speed I: Device (device, CPU, GPU, ...) Chapter 09 Need for Speed II: Precision (mixed precision training, fp16, bf16, fp8, ...) Chapter 10 Need for Speed III: Distributed (distributed optimization, DDP, ZeRO) Chapter 11 Datasets (datasets, data loading, synthetic data generation) Chapter 12 Inference I: kv-cache (kv-cache) Chapter 13 Inference II: Quantization (quantization) Chapter 14 Finetuning I: SFT (supervised finetuning SFT, PEFT, LoRA, chat) Chapter 15 Finetuning II: RL (reinforcement learning, RLHF, PPO, DPO) Chapter 16 Deployment (API, web app) Chapter 17 Multimodal (VQVAE, diffusion transformer)

12

3 Comments

Juniper Square recently released their look back at the state of venture in Q2 2024, and the data is interesting. 👉 The liquidity drought continues to stifle fundraising, with $37.4B committed to 255 funds YTD. 👉 In the current climate, established managers are securing 77% of fund value YTD, the highest concentration in the last decade.  👉 Over 63% of capital raised in 2024 so far is in funds of $500M+, the second-highest percentage in the last decade. 👉 Q2 reflects an uptick in US venture deal momentum, with quarterly deal count climbing to the highest level since Q2 2022. 👉 Q2 data shows a third consecutive upward quarter in both exit value and the total number of exits.  👉 Q2 hit a 9-quarter high in total number of exits, and the total exit value recorded was the second-best quarter since Q1 2022. The data shows that the landscape is especially competitive for emerging managers. When it comes to generating returns though, a fresh perspective can help find the most interesting deals. I wrote a bit about this last week, if you’re curious to dig into stats on unicorns at the seed stage, and the funds they’re raising from. You can check out the full report from Juniper Square here: https://lnkd.in/eN6VnY-k #emergingmanagers #stateofvc

7

Since early 2021, VC quarterly exit values have plummeted to $50B or below, a stark contrast to the six consecutive quarters of $100B+ exits before then. With IPOs dwindling and M&A activity slow, the future of venture industry exits appears uncertain. Will we see a surge in private venture-backed company acquisitions? This could be a crucial and innovative strategy to boost VC exits. Increased private acquisitions might offer a much-needed lifeline, providing a creative solution to the current exit drought in the venture capital market. #venturecapital #inspireglobalventures

3

On the back of the article from The Guardian “Banks, airlines and media outlets hit by global outage linked to Windows PCs,” it got me thinking… What would happen if AI services like ChatGPT, Gemini, etc., went down? Why can’t we use these offline instead of being connected to the Internet? Many organisations are becoming dependent on AI, raising concerns around security and privacy. We would witness significant disruptions across various sectors. Customer service, healthcare, finance, and logistics heavily rely on AI to optimise operations, provide insights, and enhance user experiences. The absence of AI would slow decision-making processes, reduce efficiency, and potentially lead to increased errors. This scenario underscores the critical importance of AI in our modern infrastructure and the need for robust contingency plans to mitigate such risks. https://lnkd.in/e8KFV6QK #AI #Technology #BusinessContinuity #RiskManagement Whitespace

19

1 Comment

I'm excited to be leading my third YC demo day fund for the S24 batch! I've been involved with YC since 2015, first going through YC myself, staying closely involved with the community for 7+ years, and culminating in working there as a Visiting Partner, where I invested in over 120 companies and helped them raise over $200M in capital. Over all this time, one thing is clear to me: YC founders are only getting better and better, and YC companies remain the cream of the crop for early stage founders. And it's not because companies come out of YC "fully baked" -- many of the best companies went through Demo Day with no revenue, or even pivoting just a few months afterwards. Yet, over 5% of this batch will likely become unicorns. This batch is appears to be the biggest one since 2021, which will make for the most interesting (and more competitive) cycle in a long time. I have opened this fund up to friends and connections who would like to join me. If you are interested in participating, click the link below for special friends-only terms! https://lnkd.in/eSKEbqQJ

25

Really cool to see #AnnArbor-based Voxel51 raising a $30MM Series B, led by Bessemer Venture Partners. What does Voxel do? Enterprise #AI models rely on huge data sets across different modalities to power outputs, but the underlying infrastructure can be overlooked. That's where Voxel plays, providing an "orchestration layer to help machine learning teams centralize, manage, and prepare the large volumes of data required to build AI applications." Did I mention that the founders have University of Michigan ties? Go Blue! https://lnkd.in/g9QpfjaH

12

Using generative AI, NVIDIA operations built an AI Planner agent, developed on NVIDIA Inference Microservices (NIM). The agent leverages LLM, NeMo Retriever and CuOpt NIM to reduce re-planning time from hours to just seconds. https://nvda.ws/4bIfS2T

18