HeyJaredTech Investments
In-depth analysis of quality and disruptive tech stocks. Examples of multi-year investments include Nvidia, ASML, Amazon, Google and Shopify. We'll be researching similar names here, as well as the key topics in the tech sector.
- Indexed issues, last 90 days
- 12
- Latest publication
- Sep 26, 2026
- Audience
- Checking…
- Earliest in this view
- Jul 7, 2026
Latest issues
Scaling Laws, Hybrid Bonding, Power Semis, TPUs in Space, Alibaba (opens the original)
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Scaling Laws & AlibabaAlibaba held its annual flagship cloud event in Hangzhou this week and the big takeaway for us was that scaling laws are alive and well. AI training times will continue to increase with recursive self-improvement and increasing model sizes. These are the highlights from Eddie Wu’s keynote:“Consider the early days of electricity: It was initially used only for lighting. In 1882, when Thomas Edison switched on the Pearl Street Station, it powered barely four hundred lightbulb
SpaceX as Nvidia’s Dominant Customer, Broadcom’s Sandbagging, Credo vs Marvell in Scale Up, SpaceX vs ASTS (opens the original)
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SpaceX as Nvidia’s Dominant CustomerElon gave a number of indications of the amount of capacity SpaceX will be deploying:“We expect to end this year with over 2 gigawatts of compute. And probably our cumulative compute online by the end of next year will be several times higher. So it may, let’s say, be closer to 10 gigawatts of compute than 5 gigawatts of compute.”And the company is looking to far exceed that number in terms of available power they’re planning to have online; which is the best
Open vs Closed Models, Snowflake, Robotaxis (opens the original)
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Open vs Closed ModelsNebius made an interesting bull case for open source models this week. Basically, enterprises don’t trust the frontier labs with their most sensitive data and so Nebius is seeing demand from enterprises to fully control their own models and infrastructure:“Customers like big corporations, they are concerned that when they use AI, they need to feed their data back to other companies. They kind of give up all of their secrets to somebody else, which then they incorporate in th
Robotics & Semis (opens the original)
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Sergey Levine is a pioneer at the intersection of robotics, reinforcement learning, and machine learning. He is recognized for shifting robotics away from hard-coded systems toward neural networks that map visual data directly to motor controls. He is a co-founder of robotics company Physical Intelligence (pi), and he detailed on the Ryan Peterman podcast the current state of the robotics field:“Initially when people started working on models for language, the dominant design was LSTMs. Some peo
Nvidia & Circular Financing, AI Outlook, and Physical AI (opens the original)
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Goldman recently went on an AI field trip to Silicon Valley and came away with the following conclusions:“We hosted our 3rd annual Silicon Valley AI Field Trip on 8/18-8/19, featuring AI companies, VCs and researchers from Stanford and UC Berkeley/UCSF. Model capabilities are continuing to improve, agents are progressing from assistance to workflow execution and monetization is expanding beyond seats toward consumption, transactions and outcomes. The strongest businesses combine proprietary data
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