Tim Tully

🌉 San Francisco's Surprising Comeback: From 'Doom Loop' to Renaissance? Recent data suggests that San Francisco, once trapped in a pandemic-induced 'doom loop', is showing strong signs of recovery. Here's what's changing: 📈 Positive Trends: - Population Growth: Net gains over the past two years, with domestic in-migration positive for the first time since 2012. - Housing Market: Median home sale prices up 1.2% YoY to $1,427,500 in June. - Job Growth: The Bay Area added 7,400 jobs between January and June. Downtown Revival: Foot traffic beyond typical work hours has recovered to over 90% of pre-pandemic levels. - Crime Reduction: Property crime down 32% and violent crime down 14% in Q1 2024 compared to Q1 2023. - AI Boom: The city is positioning itself as a hub for the AI revolution. 🚧 Ongoing Challenges: - High office vacancy rates - Homelessness and drug crisis - Lagging tourism and business travel 🔑 Key Initiatives: - "Vacant to Vibrant" program offering free rent to businesses in empty storefronts - Increased police patrols and encampment sweeping - Crackdown on open-air drug dealing 💡 Expert Insight: "The rising AI empire is giving the city a new edge. Funding, talents, and culture related to the AI revolution will help the city turn the corner." - Lu Chen, Senior Economist at Moody's Analytics 🤔 What's Your Take? Are these positive trends sustainable, or is it too early to declare a comeback? How can other cities learn from San Francisco's recovery strategies? What role will AI play in reshaping urban economies, particularly in tech hubs? https://lnkd.in/gCnPCBRU

14

1 Comment

Some additional charts on the aggregate hyperscaler data from Q1. The charts below show 1) The aggregate net new ARR added on q quarterly basis. Q1 is always a seasonal low 2) The YoY growth in net new ARR in Q1. Q1 '23 was the "bottom" with AWS actually adding negative net new ARR (ie they shrunk), so the YoY comp is the "easiest" for the aggregate bucket.

20

LLMs are trained on internet-scale data. But to make AI work for work, models need to be grounded in your enterprise data -- a much harder problem than meets the eye! How do you connect to all your data sources and ingest them frequently enough while managing compute/storage costs? How do you make sure that you only show users results from documents they have access to? How do you rank results without internet-scale click and link data? How do you process the content of documents that are often hidden in PDFs and presentations? These are tricky problems, and it's why enterprise search didn't work for nearly a decade, until Glean came along. Turns out it's the exact same set of challenges needed to give LLMs the right context to work their magic on your enterprise content. Glean spent 5 years building the ingestion, search, and ranking infra needed to solve this problem well. This has given them the right to run the "Work AI" race and delight users at work. CEO Arvind Jain shares more on the latest episode of Training Data. Listen here, or wherever you get your podcasts: YouTube: https://seq.vc/ytd Apple: https://seq.vc/pit Spotify: https://seq.vc/jnz 

204

10 Comments

Worth reading: How the Apache Arrow Format Accelerates Query Result Transfer by Ian Cook One of the hidden problems of intersystem communication is transcription of data formats. Ian does a wonderful job of explaining the "why" of Apache Arrow as well as the "how" of its advantages. Read on...

8

We're launching the inaugural edition of Beyond Benchmarks, a deep dive into the metrics and trends observed across the early-stage enterprise cloud market. This is the first look at some of the business data around GenAI in SaaS. Some initial observations: 1) 60% of SaaS companies have already integrated GenAI into their offerings (60% of these as part of their current product and 40% as a new product), and an additional 20% are planning to do so this year. Almost half aren't monetizing these features. Those that are are primarily experimenting with both usage-based and flat fee pricing models. 2) Most companies are utilizing OpenAI as their primary LLM, but many are experimenting with multiple models - and we are noticing an early trend towards intelligently routing GenAI inference requests to different models based on cost, performance, and security. 3) Though we are in the initial innings of GenAI, we are seeing some positive signals - companies that implemented GenAI had 7% higher NDR than those that did not. Still early days, but we'll be doing this benchmarking report regularly to track and share how things progress in this new era. Link to report in comments.

104

6 Comments

🔔 Google to Vacate 300KSF at One Market in San Francisco; pushing CBD Availability Up ~.5% 🔔 🌁 One Market Plaza, a "trophy" office complex in San Francisco, faces significant change as Google prepares to leave its 300,000-square-foot space in Spear Tower by April next year. This move follows Visa's earlier departure to Mission Rock, highlighting a shift in tenant dynamics for this iconic property. 🏢 Despite vacating Spear Tower, Google will maintain a presence in the complex, retaining space in the Landmark building. This adjustment is part of Google's broader strategy to realign its real estate to better fit the hybrid work model, emphasizing efficiency and flexibility. 📉 The departure comes at a time when office availability in San Francisco have hit record highs of over 36%, yet One Market Plaza continues to command rents about 20% higher than other premium office buildings in the city. This resilience in rental value underscores the enduring appeal of top-tier office locations. 💼 The property owners, after successfully renegotiating a $975 million loan extension, are proactively engaging with potential new tenants to fill the upcoming vacancy. One Market Plaza remains a key asset, now with a 92.5% occupancy rate, despite the broader market's volatility. 🔄 This development reflects broader shifts in urban office space use and strategic real estate planning in the wake of the pandemic. It signals important trends that companies and real estate professionals must navigate as they adapt to new work patterns and economic landscapes. https://lnkd.in/gzdyE2zx

21

➰ 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

15

1 Comment

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

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

3

When adding all of their clients to a new Confluent Cloud-based architecture, interactive ad-tech platform Skai realized their initial design would require 90,000 topics in order to accommodate everyone. Using many-to-one relationships between producers and topics, and between consumers and topics, Skai devised an ingenious architecture that reduced that number to 1,800 topics. Learn how they did it in a new blog: https://cnfl.io/3WIEQcf

41

2 Comments

Old school and probably not popular but I still believe products should be customer-satisfaction focused/led rather than technology-led. Use cases for AI should be byproducts of the product improvement process primarily. The thing though is that founders need to fundraise so they're likely to sprinkle some AI on their decks to even look serious. Not sure that's how the most enduring companies have been built. Of course, if sources of capital become AI-biased, founders have little choice. Happy to keep an open mind and dive in when a use-case that can 10x customer experience for Good Tenants customers and users shows up.

5

You know I always appreciate Bill Blain’s thoughts; his recent newsletter reminded me of a wonderful New Yorker cartoon, “What Lemming’s Believe.” it is a wonderful piece of art that fits well with Bill’s recent newsletter. I do not always agree with his thinking, but I always appreciate his writing and thinking - a recommended subscription. My personal sense is that Meta and Google are terrified of what OpenAI and Microsoft are doing due to the potential impact on additional revenues (though I feel Meta and Google's reactions will eventually accelerate revenue decline as everyone will ultimately be shouting, which will mean no one will listen) - their response has been a massive investment in LLM related technology, as well as a push to give the models away (in my view) to take the oxygen out of the room for any other aspiring AI startups. Consider the parallels with Zoom. Zoom charged for video, Google’s response was to offer free video for 30 minutes, Microsoft made similiar moves with teams which they bundled in office. Meta is playing the same game with its LLM models. New entrants cannot compete with free; Meta, Google, and others will simply wait and mop up everything after the money is spent; hence, spending is a tad high right now. My personal sense is that Microsoft is very well-positioned, and I’ve never sold my stock. Why? It is a well-run and ecologically diverse company. Google and Meta are not ecologically diverse from a revenue perspective. This means that they have to fight and kill to maintain their ecological/ market niche. Any change in the environment will cause their costs to consume the host. A.K.A BlackBerry versus the iPhone. The difference per unit was a $149 dollar BES license versus no BES license for the iPhone. For a bank, that’s a $500,000 difference in license renewal cost. BlackBerry’s costs killed them, not the iPhone - specifically their Management costs. This reminds me of R. H. Donnelley (RHD), Yellow Pages; more than half a million advertisers paid $3,500 a year for space in the Yellow Pages as recently as 2006, and total circulation reached 80 million copies. The RHD CEO’s presentation to investors in March 2006 was titled “Positioned for Continued Success.” Just three years later, in May 2009, R. H. Donnelley went bankrupt. That, to me, is why Meta and Google are spending money from a gushing fire hydrant - they have one revenue source - advertising. They must kill to maintain that revenue stream; they have none to replace it. To be clear, this neither good nor bad, it simply is. What Lemmings believe by Robert Mankoff. https://lnkd.in/g-XhWFZg

11

3 Comments

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

16

Looking forward to sharing how we at basys.ai are leveraging Generative AI to tackle healthcare’s biggest challenges. PS: Also looking forward to sporting my basys vest in the #BayArea PPS: What I’m not looking forward to is the second cross-country flight in less than a week. #GenAI #BasysAI #GenerativeAI

21

At #OffsetSymposium2024, and couldn’t agree more with Corey Jaskolski that wide-spread #cloud adoption across #DOD allows startups to scale more broadly, lowers their costs, allows them to move faster, and ultimately delivers more, saving the limited taxpayer dollars we have for #nationaldefense.

8

Seismic’s AI enablement assistant, Aura Copilot, is now available for early access. Teams can now get faster access to answers and content, automate tedious tasks, and gain insights for better business decisions. Aura also now integrates with Microsoft Teams and Microsoft 365 Copilot to give teams in-the-moment answers and content recommendation. https://lnkd.in/d_mSbDXK

44

1 Comment

Anthropic Partners with Palantir and AWS to Target Defense Sector with AI Solutions - Anthropic has teamed up with Palantir and Amazon Web Services (AWS) to offer its advanced AI technology to defense customers, focusing on secure and strategic applications. - This collaboration seeks to leverage Palantir's data integration capabilities and AWS's cloud infrastructure to enhance AI deployment within defense environments. - By aligning with these industry leaders, Anthropic aims to extend its reach into the defense sector, providing sophisticated AI tools designed to support complex, mission-critical operations. - The partnership underscores the increasing intersection of AI technology and defense, highlighting the demand for cutting-edge solutions in national security contexts. #DefenseTech #AIInnovation #AnthropicAI Read more: [https://buff.ly/3NUTxVD]

2

🌟 From Raw Data to Behavioral Predictions—Effortlessly What if AI deployment didn’t require months of preparation? With BaseModel.ai now on the Snowflake Marketplace, you can transform behavioral data into predictions in just a few clicks. ✅ Rapid Deployment: Build and deploy models in a week.  ✅ Scalable Flexibility: Create multiple models for diverse use cases.  ✅ Privacy Guaranteed: Data never leaves the secure Snowflake environment. Say goodbye to complexity and hello to actionable insights. AI for behavioral data has never been this simple. 👉 Try BaseModel.ai Today  #AI #MachineLearning #BehavioralData #BaseModel #Snowflake #Synerise 

39

4 Comments

The State of the Cloud talks about a lot of hot topics, but one that sticks out to me is Voice AI. This is something that I have seen our portfolio company Ribbon leveraging in their Recruit AI product. Their idea was to leverage voice AI to optimize and make phone screen interviews more efficient. For firms that are hiring, this has been a game changer for them to manage a better candidate experience. Voice AI will soon be seen everywhere including call centers. I personally am excited to see the next wave of new companies leveraging Voice AI in new use cases. More on this topic and the State of Cloud in the link 👇

11

1 Comment