Sign in to view Sunny’s full profile
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Palo Alto, California, United States
Contact Info
Sign in to view Sunny’s full profile
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
12K followers
500+ connections
Sign in to view Sunny’s full profile
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
View mutual connections with Sunny
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
View mutual connections with Sunny
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Sign in to view Sunny’s full profile
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
or
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Experience & Education
-
Groq
** ** *********, **** ** ********** *****
-
***** ********
***** ********
-
********** ************
**-******* *** ***
View Sunny’s full experience
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
Welcome back
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
View Sunny’s full profile
Sign in
Stay updated on your professional world
By clicking Continue to join or sign in, you agree to LinkedIn’s User Agreement, Privacy Policy, and Cookie Policy.
New to LinkedIn? Join now
Other similar profiles
-
Adam Tachner
Palo Alto, CAConnect -
Jonathan Ross
CEO & Founder, Groq®
Palo Alto, CAConnect -
Mohsen Moazami
United StatesConnect -
Tim Sears
Palo Alto, CAConnect -
Jose M.
Palo Alto, CAConnect -
John Barrus
Menlo Park, CAConnect -
Bryan Banisaba
San Francisco Bay AreaConnect -
Michelle Donnelly
San Francisco, CAConnect -
Estelle Hong
Mountain View, CAConnect -
Jon Tait
Los Altos, CAConnect -
Mustafa Suleyman
Palo Alto, CAConnect -
Jason Calacanis
San Francisco, CAConnect -
Chamath Palihapitiya
San Francisco Bay AreaConnect -
Amr El-Ashmawi
Los Gatos, CAConnect -
Daniel Loman
Albany, New York Metropolitan AreaConnect -
Ariel Poler
San Francisco Bay AreaConnect -
Jon Bischke
Austin, TXConnect -
Giorgos Zacharia
Greater BostonConnect -
Ben Colman
New York, NYConnect -
Alan Chiu
Palo Alto, CAConnect
Explore more posts
-
Lucas Dickey
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
5
-
Benjamin Wolkon
"Advanced computing is starting to serve utilities..." As the rise of AI is contributing to a near-doubling of five-year energy load forecasts (from 2.6% to 4.7% growth), AI is also at the core of some of the innovation to solve the biggest problems in climate and energy. A couple of weeks ago I was in a room of investors who were asked if it's "too early" to be investing at the nexus of AI and climate. I was surprised to even hear the question, because we've been doing it for years. This article from Utility Dive highlights three companies in which MUUS Climate Partners was an early investor: - BrightNight, which created an advanced simulation tool to optimize the design and operations of clean energy projects; - Amperon, which has built the world's most accurate energy demand forecasting system; - Utilidata, which has partnered with NVIDIA to deliver the first distribution system AI platform. If you're interested in the AI-climate nexus (and not just the buzzwords, but the actual solutions being built and deployed), this article might be of interest. https://lnkd.in/evkkY4nX
12
1 Comment -
Garnet S. Heraman
Science-fiction is inherently speculative. Author George #Orwell of ‘#1984’ predicted concepts such as doublethink, little earbuds and society’s obsession with the black mirror screens that dominate our lives — and according to the BBC, novelist and short story author JG Ballard, of “High-Rise” and “Crash” fame, has predicted the current tool and cultural fixation of #GenerativeAI in the modern society — only he didn’t just speculate them within a story, he is actually one of the first use-cases of a generative AI used in a creative context — Ballard was so fascinated with the growing technological advancement of computers that he used one to compose poems, essentially the precursor to what we have now with ChatGPT. Today, the debate about the creative use of generative AI and its value on creative industries is an extremely fraught and controversial topic, but if controlled in a space that doesn’t replace human labor or try to equate itself to traditional art forms, it is interesting to see what computers can do and how they are creatively limited in comparison. Ballard’s two poems, The Yellow Back Novels and Machine Gun City are generated, and both include notes on how Ballard achieved producing them. Regardless of quality (Ballard himself probably wouldn’t describe these two poems as his best work), it is interesting to see primitive versions of the technology that we utilize on the daily today, and how these moral conversations that concern them would continuously evolve.
1
1 Comment -
Will Grannis
For all of you space enthusiasts, excited to share the results of some work over the last 5 months between my friends at B612 and Google Cloud. Using GKE, BigQuery and Cloud Storage, Edward Lu and his team, researchers from the University of Washington along with Massimo Mascaro and some folks from Google, were able to comb through existing archived astronomical surveys and discover 27,500 new high confidence asteroid discovery candidates, including more than 100 that are classified as "Near Earth" 😳 And with the data pipelines established, we can now move to using AI to automate classification and risk based analysis at a rate that will allow us to match the pace of cosmological data growth with insights and actions. As Ed put it, being able to match the photonic capabilities of telescopes with the electrons in data centers at massive scale promises to unlock more discoveries like this, including supernovae explosions, minor planet discoveries and maybe even help us avoid the wrong kind of impacts ;) https://lnkd.in/gJa72Zn2 https://lnkd.in/gJRnH5pB
138
9 Comments -
Morgan Cheatham
Open-source models can be a strong lever for increasing gross margins at AI companies, especially those that have hefty cost structures (e.g., enterprise sales orgs that require significant customer success or implementation resources, as well forward-deployed AI services models common in healthcare and life sciences). One of many reasons to maintain a modular and flexible stack with minimal dependencies when building an AI company. More on the importance of flexibility in the AI stack: https://lnkd.in/eA2XATRk h/t Delip Rao #ai #artificialintelligence #generativeai #healthcare
50
6 Comments -
Sim Desai
Some unicorns and late-stage VC-backed companies restrict their employees from selling their stock, often at the request of their boards of directors. Not this one. Andrew Feldman and his executive team at Cerebras Systems (a high-flying AI chip startup mounting a challenge to the likes of NVIDIA and Groq) have been willing to recognize the blood, sweat and tears that employees with vested options have put into building this impressive business, by allowing them to sell their shares in the private market. This is not just great news for current and former Cerebras employees but also for the company and its investors! Why? Liquidity typically leads to higher stock pricing, making it more attractive to investors. How so? The short answer is that when a stock is more liquid, its riskiness declines. When risk goes down, so does the discount rate (the cost of capital) that investors use to price the asset. When the discount rate goes down, all else equal, the price should go up! This enhanced liquidity and pricing can help a company with fundraising valuations, consolidating the cap table before an IPO, and bridging the valuation gap between an illiquid private market and a very liquid public market. Congratulations to Andrew and the Cerebras team for delivering on your promise to your employees and investors by allowing a liquid market for your stock. And bravo to your board members (which, according to PitchBook include Eric Vishria of Benchmark , Brad Gerstner of Altimeter, Steve Vassallo of Foundation Capital, Lior Susan of Eclipse, Thomas Laffont of Coatue, and Pierre Lamond) for supporting your vision! #secondarymarket #privatemarket #marketplace #unicorns #stockoptions
89
7 Comments -
James Wu
We're thrilled to announce M12's participation in DatologyAI's Series A! Datology is a leading data curation platform that empowers businesses to unlock the true potential of their data for AI and machine learning initiatives. As the field of AI continues to evolve, data curation will play an increasingly critical role. We believe Datology is at the forefront of this revolution, providing the tools and expertise necessary to build robust, reliable, and impactful AI models. We're already seeing SLM (small language models), including Microsoft phi-2, tout "data curation" as a major driver of improved model performance and accuracy. It's no secret that clean, curated data is the fuel for high-performing AI models. However, the status quo is to throw (big) data at the problem. Datology re-imagines how models are pre-trained by shifting the focus from parameters to data quality and data accuracy at the data curation phase. While we think big data will remain the foundation, we also believe curated, contextualized data will drive the next frontier of AI advancement. Congrats Ari Morcos Bogdan Gaza Matthew Leavitt! M12, Microsoft's Venture Fund Michelle Gonzalez Michael Stewart Todd Graham Peter B. Tina McNulty Valentina Escudero Jose Clautier Noah Bradford #data #microsoft
144
8 Comments -
Paul Hsu
Vishal Sachdev highlights the strategic integration of open source and proprietary tech in architecting tech stacks, developer ecosystems and resulting business models. The world class companies effectively balance value commoditization in open source and value capture in proprietary tech. This is the strategic challenge for companies operating in #blockchain and #AI. I believe those who operate at the intersection of blockchain *and* AI stand to win this strategic battle...
3
1 Comment -
Joanne Chen
To build a multi-agent system, start simple, validate your design, then gradually scale. When I spoke to Chi Wang, the creator of AutoGen, he explained why. Deploying one or two agents at first allows builders to evaluate and refine the core design and interaction patterns before introducing additional complexity. This method also streamlines debugging and optimization because it makes it easier to trace issues back to specific agents. Our full conversation here: https://lnkd.in/gEKmExu4
15
1 Comment -
Shaler Houser
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 -
Jon Krohn
Solitary LLMs are impressive, but several can work together as a Multi-Agent System to astounding effect and overcome solo LLM (GPT-4o, Claude 3, Gemini) limitations. Hear all about it in today's "Five-Minute Friday" episode. In a bit more detail: • In recent weeks, OpenAI's GPT-4o and Google's Project Astra showcased A.I. agents that engage in humanlike conversations and analyze real-time video. • Despite such impressive capabilities, single A.I. agents still struggle with many categories of complex tasks. • Thoughtfully linking individual LLMs together into a Multi-Agent System (MAS) enables them to work together, assign tasks, build upon each other's work, and deliberate to find solutions, in aggregate exceeding the capabilities of a single LLM on its own... often without any decrease in compute efficiency. • As an example, a DARPA experiment demonstrated 3 agents (named Alpha, Bravo, Charlie) collaborating to defuse (virtual!) bombs efficiently. • In an Massachusetts Institute of Technology study, two chatbots solving math problems outperformed a single agent through dialogue and updating each other's answers. • Microsoft developed a software-writing MAS with specialized roles (Commander, Writer and Safeguard; see the image for this post) wrote code 3x faster without sacrificing accuracy. • As always, there are potential risks, e.g.: illogical solutions cascading through the team, agents getting stuck in loops, and malicious exploitation. • Commercial interest in MAS is accelerating, with frameworks like AutoGen and Camel making it straightforward for you to get started with MAS today yourself. What in your industry could be automated or improved by MAS where single-LLM approaches aren’t sufficiently effective? 🤔 For more detail on all of the above, check out today's episode (#788)! The Super Data Science Podcast is available on all major podcasting platforms and a video version is on YouTube. #superdatascience #machinelearning #ai #llms #multiagentsystems
52
4 Comments -
Marvin Liao
"So getting back to NVIDIA, I don’t see any force stopping the juggernaut in the next few years, other than a huge decline in the need for AI compute, and that seems unlikely. Any startup competitor could easily be acquired by NVIDIA for tens of billions of dollars and it would barely be material given NVIDIAs market cap. And while the other major chip companies are mounting a challenge, particularly AMD, the demand for GPUs is so great, and will be for the next few years, there is room for massive growth for multiple players. When NVIDIA eventually slows down, I suspect it will come from one of two areas. The first is a surprising shift in market use cases. Given the long development cycles of computer chips, it’s hard to be as responsive to the market demands as software companies can be. And product designers have to choose some level of predictability and reliability in their components and their partners, which is why they favor proven tech over innovative new designs most of the time. But the way NVIDIA benefited because their chips for graphics cards happened to be a good match for new AI workloads - I think something similar could happen to slow them down. Some new popular AI workload will be a better fit for something other than a GPU, but a chip that is already established in the market in other ways. Or secondly, it comes from a company that is building their own chips and decides to get into the broader semiconductor business. This means Apple, Amazon, Facebook, or most likely - Google. But all those companies, even if they can compete technically with NVIDIA, lack the infrastructure to sell and support chips and those who develop them. Building those capabilities will be slow." https://lnkd.in/dFpj5hqv
1
1 Comment -
Chinar Movsisyan
💡 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
-
Faraz Thambi
Bowen Yang from Cohere will dive into the world of long-context models and how we can push the boundaries of transformer architectures. At TMLS2024 we'll explore: ✅ Scaling Transformers: Techniques for handling longer inputs while maintaining efficiency. ✅ Challenges & Solutions: Examining the modelling and framework hurdles we face, along with potential solutions. ✅ A Range of Approaches: We'll delve into methods across data, modelling, and framework levels. ✅ Training, Evaluation, & Inference: Covering the entire NLP pipeline for long context tasks. This panel promises to be a valuable resource for anyone interested in pushing the limits of language understanding. See the full abstract here: https://lnkd.in/gwSRjPjz #NLP #Transformers #LongContext #MachineLearning Toronto Machine Learning Society (TMLS)
29
-
Damir Ibrahimagic Kopinic
🌟Innovative VC Firm Overcomes Exits Drought with Secondary Sales🌟 ⛵Navigating a challenging landscape where exits are scarce, Santa Barbara Venture Partners (SBVP) has pioneered a novel approach to sustain its growth and attract investors for its second fund: secondary sales. Instead of waiting for traditional exits like IPOs or acquisitions, SBVP opted to sell shares of its portfolio companies, demonstrating its ability to generate returns for investors and stand out in a competitive market. 🎤According to Dan Engel, founder and managing partner of SBVP, these secondary transactions have been a game-changer, sparking investor interest and bolstering the firm's credibility. By leveraging its recent successes, including a lucrative stake in sports-betting company DraftKings Inc.' acquisition of digital lottery app Jackpocket, SBVP seized the opportunity to return profits to its limited partners (LPs) and pave the way for its second fund. 💡Engel highlighted the challenges faced by young VC firms in raising subsequent funds, particularly amid a downturn in exit activity and heightened investor scrutiny. With traditional exit routes becoming increasingly elusive, the pressure is on for firms to demonstrate tangible returns and establish a track record of success. ✨"For us, secondary sales have been a game-changer. They've helped us return profits to our LPs and attract investors for our second fund," said Dan Engel. 💰For SBVP, the decision to pursue secondary sales was driven by the need to provide liquidity to LPs and validate its investment thesis in the eyes of prospective investors. By strategically offloading portions of its holdings in high-performing portfolio companies like Bark Technologies and Rad AI, SBVP not only generated substantial returns but also bolstered investor confidence in its ability to deliver results. ⚠Despite the complexities and potential stigma associated with early share sales, Engel emphasized the importance of prioritizing investor returns and seizing opportunities to unlock value for stakeholders. With a focus on profitability and transparency, SBVP remains committed to its mission of delivering sustainable growth and maximizing returns for its LPs. 🔍 "Returning profits to our investors is our top priority. By strategically selling shares, we're proving our commitment to delivering results and driving value for our stakeholders," added Engel. As SBVP continues to explore secondary transactions and expand its investor base, the firm stands as a testament to innovation and resilience in the face of market challenges. 🚀 ✅ Looking to raise capital for your #fund and increase the international pool of your LP #investors? 🤝 Need warm #LP introductions? 📝 Selling #secondaries to increase liquidity? 🧐 Looking for co-investments? ▶ G+QUANT's link for inquiries and fund decks: https://lnkd.in/gjC_EuTE #VCInnovation #SecondarySalesSuccess #InvestorReturns #ValueCreation
2
-
Josh Felser
I find it hard to believe that with millions of EVs entering the market and the proliferation of AI compute that PGE is actually going to have excess capacity in 2040 without any additional generation from 3rd parties. I am also curious if there are enough transmission lines and if PGE views that as someone else’s problem. Maybe they are planning on AI and ACTUAL figuring it all out! https://lnkd.in/gybsMmaw
10
5 Comments -
Matt Ober, CAIA
What a month of dataset releases on Initial Data Offering The momentum going into the summer is hot! All leading up to the premium IDO newsletter which will become available in the coming days! Lots of great features in the premium newsletter. Stay tuned. Few of my favorites this past month. - China Beige Book (CBB) Featuring monthly releases, China Beige Book tracks over 100,000 unique data series, allowing clients to anticipate major macro swings and credit events - Vumonic Datalabs E-receipt Data (Global): Global E-receipt Data Which datasets caught your eye?
22
4 Comments -
Ashu Garg
As we look ahead to 2025, it's becoming clear that the future of enterprise AI lies in compound systems, not monolithic models. Compound AI systems combine multiple models that work together iteratively, coordinating and leveraging external tools to evaluate, refine, and improve their own results. 🔄 The benefits are clear: ☑ Better performance than individual models ☑ Faster and less expensive iteration ☑ Granular access controls on sensitive data ☑ More reliably ensure that models behave as intended ☑ Flexible performance-cost optimization Early examples like AlphaCode 2, LLM Debate, and CoT-SC are already showing impressive results. 📈 As we move towards 2025, compound AI systems will become increasingly critical for enterprises looking to deploy AI at scale reliably, securely, and cost-effectively. 🎯 Check out my latest B2BaCEO newsletter for a detailed look at where AI is headed and what it means for founders: https://lnkd.in/gRrzX9nq h/t to Berkeley Artificial Intelligence Research and my colleagues Jaya G. Andrew Han Courtney Fiske for their research help
65
6 Comments
Explore collaborative articles
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
Explore More