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neil

T2 · manager / operator

Neil is the co-founder and CTO of K2 Space, leading engineering on the Mega-class satellite platform. He oversees development of 20kW Hall thrusters, deployable solar arrays, high-voltage power systems, and radiation-hardened electronics for operation across LEO, MEO, GEO, and deep space.

32 calls·14 names·47% bull·last heard last month·Kleiner Perkins+2
track record

no scored calls yet — needs a stated position or a categorical verdict, with a matured window vs SPY

top calls

highest conviction · one per company
1sthigh conviction
$AMDAdvanced Micro Devicesposition

Buying AMD aggressively as market sleeps on programming difficulty

AMD chips offer great compute per dollar but are underutilized because vendors invest less in kernel optimization; Sail Research builds software to unlock that alpha and is buying all available supply.

Invest Like The Best2026-08episode →
2ndhigh conviction
$SAILSail Researchposition

Sail Research builds 'token factory' targeting 1000x cheaper intelligence via heterogeneous chips, distributed data centers, and scavenged power

By optimizing software for throughput (not latency), buying undervalued chips (AMD, TPU, Trainium, custom), deploying 1MW distributed data centers with 95% uptime tolerance, and pairing with intermittent renewable power, Sail Research aims to drive token cost down 3-6 orders of magnitude.

Invest Like The Best2026-08episode →
3rdhigh conviction
$MUMicron Technology

HBM supply bottleneck structural; memory makers burned by cycles will not add capex fast

HBM capacity is the hardest bottleneck to expand — Micron, SK Hynix, Samsung have been burned by cyclical downturns and resist massive capex, so shortage persists and forces system-level efficiency innovations elsewhere.

Invest Like The Best2026-08episode →

most discussed · click a bar to filter

  • $CBRS
  • $GROQ
  • $INTC
  • $AMD
  • $SAIL

recurring themes

  • Memory & Storage3
  • AI Infrastructure2
  • AI Hardware & Chip Architecture2
  • Semiconductors2
  • Data Center Infrastructure2
32 total
$K2-SPACE
K2 Space
HIGHneil·Kleiner Perkins·2 months ago·K2 Space: Building Bigger
K2 Space CTO argues physics demands larger satellites for superior mission performance
Satellite mission performance is fundamentally constrained by power, aperture, and mass; K2's approach maximizes all three via 20kW Hall thrusters, giant deployable solar arrays, and radiation-hardened electronics at low cost.
"Physics really wants satellites to be bigger, right? So, from a payload perspective, all of the mission performance comes down to a combination of three things: power, aperture, w…"
1:13
$CBRS
···
Cerebras
MEDneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper
Cerebras wafer-scale SRAM excels at MLP weights but KV cache capacity forces hybrid GPU pairing
Cerebras' massive on-chip SRAM (21 PB/s bandwidth) is ideal for compute-bound MLP layers, but dynamic KV cache growth requires off-chip DRAM capacity, so optimal architecture pairs Cerebras for weights with GPUs for attention.
"Cerebrus has a very fast memory access for something like a matrix multiply and it's really good to host the the MLP the the weights essentially on the Cerebrus chip but the GPU h…"
32:23
$GROQ
Groq
MEDneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper
Groq and Cerebras seen as accelerators for hybrid inference, not standalone replacements
Low-latency specialists like Groq and Cerebras will serve as accelerators paired with traditional GPUs that provide off-chip memory capacity for KV cache, creating a heterogeneous inference stack.
"Crisis and Grock and maybe a couple others, you should think of them as accelerators. What they are really good at is being used in conjunction with an more traditional GPU like d…"
30:58
$OPENAI
OpenAI
MEDneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper
Closed-source labs' 3-6 month lead may not sustain premium as enterprise adoption lags
Frontier labs pay huge premiums to stay months ahead, but enterprises adopt slowly (still on older models), and open-source diffusion via distillation and AI-generated code is inevitable, eroding the moat over time.
"the labs pay an immense premium to be 3 to 6 months ahead of of everything else... I don't think the premium for being 3 to six months ahead is going to last that long... enterpri…"
70:22
$INTC
···
Intel
MEDneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper
Intel's western leading-edge process only ~2x behind TSMC, reducing geopolitical risk
If TSMC access is lost, Intel's best process nodes are at worst 2x worse performance-per-watt — a far smaller gap than chip-industry dialogue suggests, making supply shock manageable.
"the best processes that we have in the west uh like Intel not that far behind at worst like maybe 2x uh worse performance per watt and the gap is just far smaller than than you wo…"
77:10
$MU
···
Micron Technology
HIGHneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper
HBM supply bottleneck structural; memory makers burned by cycles will not add capex fast
HBM capacity is the hardest bottleneck to expand — Micron, SK Hynix, Samsung have been burned by cyclical downturns and resist massive capex, so shortage persists and forces system-level efficiency innovations elsewhere.
"There's no easy way to bring on a lot more fabs of memory and those guys have been so it's going to be a while until we... The boys in Boise don't uh don't love huge capex for for…"
79:55
$AMD
···
Advanced Micro Devices
HIGHneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper· position
Buying AMD aggressively as market sleeps on programming difficulty
AMD chips offer great compute per dollar but are underutilized because vendors invest less in kernel optimization; Sail Research builds software to unlock that alpha and is buying all available supply.
"AMD, I think great chips overall. The challenge is that people don't um understand how to program them very well. ... That's music to my ears. I'm very happy for them to sleep on…"
46:16
$SAIL
Sail Research
HIGHneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper· position
Sail Research builds 'token factory' targeting 1000x cheaper intelligence via heterogeneous chips, distributed data centers, and scavenged power
By optimizing software for throughput (not latency), buying undervalued chips (AMD, TPU, Trainium, custom), deploying 1MW distributed data centers with 95% uptime tolerance, and pairing with intermittent renewable power, Sail Research aims to drive token cost down 3-6 orders of magnitude.
"My job is to make the tokens as cheap as humanly possible. I will achieve that and I will do it through every layer in the stack available to me. I love the supply side levers. I…"
73:01
$NVDA
···
Nvidia
MEDneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper
Ex-Nvidia engineer sees slowing perf-per-watt gains, geopolitical risk overblown
Nvidia remains best-in-class for both latency and throughput today, but performance-per-watt scaling across process nodes (TSMC 5nm to 2nm) is minimal, and western fabs like Intel are only ~2x behind, making TSMC dependence less catastrophic than consensus fears.
"I am bullish on Nvidia in the short term. And you know, Nvidia, you should never bet against them. They're always going to reinvent themselves. But like fundamentally I think one…"
76:31
$DEEPSEEK
DeepSeek
MEDneil·Invest Like The Best·last month·Ex-NVIDIA Engineer: Why AI Is About to Get 1000x Cheaper
DeepSeek publishing order-of-magnitude KV cache compression advances yearly
DeepSeek's open research on KV cache compression demonstrates rapid algorithmic progress (10x+ per year), signaling massive remaining headroom to reduce memory bandwidth pressure in inference.
"Deep Seek certainly publishes really interesting work to compress that further and further. And they're making good progress. And I think the fact that they're able to make order…"
64:36
9
AI Agentstailwind
Background agents with self-administered token budgets will consume 90% of inference compute within years
Human-in-the-loop chatbots saturate human attention; proactive agents running for hours/days on verifiable tasks (coding, research, security) have unbounded token demand and will shift inference spend from latency-sensitive to throughput-optimized workloads.
9
AI Infrastructuretailwind
Inference shifting from latency-optimized chatbots to throughput-optimized background agents
As agents run hours-long tasks autonomously, the GPU's throughput-oriented happy path (large batches, high utilization) becomes dominant over latency-optimized interactive serving, unlocking 10x+ efficiency gains.
9
AI Hardware & Chip Architecturetailwind
Shift to background agents favors throughput over latency, enabling diverse chip architectures
As AI workloads shift from interactive chatbots to long-horizon background agents, the GPU trade-off favors throughput-optimized serving, allowing use of chips without high-speed interconnects (like AMD, custom ASICs) and unlocking heterogeneous compute fleets.
9
AI Hardware & Chip Architecturetailwind
Throughput-optimized inference stacks will replace latency-optimized chatbot stacks as agents move to background
The shift from interactive chatbots to long-horizon background agents eliminates the latency-throughput tradeoff, enabling rack-scale batch processing that maximizes GPU utilization and lowers cost per token by orders of magnitude.
9
Semiconductorstailwind
Heterogeneous chip fleets and software-defined hardware arbitrage replace Nvidia monoculture
No single chip wins all workloads; the optimal inference stack mixes Nvidia (NVLink/latency), AMD (compute/$), custom ASICs (TPU/Trainium), and accelerators (Cerebras/Groq) via a software layer that routes each model component to its comparative advantage.
9
Data Center Infrastructuretailwind
Distributed 1MW data centers on intermittent renewables viable for background inference
Background agent workloads can tolerate 95% uptime, enabling use of small (1MW) data centers powered by intermittent solar/wind without expensive redundancy, unlocking stranded power and land across the US.
9
Memory & Storagetailwind
KV cache compression is the next order-of-magnitude efficiency frontier; current storage is uncompressed by 10-100x
The KV cache grows dynamically with context length and currently stores many kilobytes per token at far above its information entropy; DeepSeek and others are achieving order-of-magnitude compression yearly, signaling massive remaining headroom.
9
AI Economics & Business Modelstailwind
Token cost on track for 1000x decline, enabling trillion-token-per-day per-user workloads
Current $5M/day for 1T tokens (OpenAI pricing) falls to ~$5k via hardware arbitrage, software efficiency, distributed infra, and scavenged power — making 'abundant intelligence' economically viable for proactive agents, deep research, and scientific discovery.