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A 340 page huge report on AI trends - released by @bondcap Some wild findings from this report. 🧵1/n


🧵2/n Meta’s Llama Downloads Exploded 3.4× in Eight Months. an unprecedented developer adoption curve for any open-source LLM. bondcap. com/reports/tai


🧵3/n AI Chatbots Now Mistaken as Human 73 Percent of the Time In Q1 2025, testers mistook AI responses for human replies 73 percent of the time in Turing-style experiments. That’s up from roughly 50 percent only six months earlier—showing how quickly models have learned to mimic human conversational nuance


🧵4/n <a target="_blank" href="https://x.com/rohanpaul_ai/status/1928727657405100340" color="blue">x.com/rohanpaul_ai/s…</a>

🧵5/n <a target="_blank" href="https://x.com/rohanpaul_ai/status/1928731224215851159" color="blue">x.com/rohanpaul_ai/s…</a>

🧵6/n <a target="_blank" href="https://x.com/rohanpaul_ai/status/1928731841957097774" color="blue">x.com/rohanpaul_ai/s…</a>

🧵7/n Annual AI Inference Token Revenue Potential Jumped from $240K to $7 Billion in 8 Years In 2016, a $1 billion-scale data center could handle about 5 trillion inference tokens per year (~$24 million token revenue). By 2024, that same $1 billion facility could process ~1,375 trillion tokens (theoretical revenue ~$7 billion)—a 30,000× shift in earnings opportunity


🧵8/n inference costs per million tokens plunging nearly 99.7% from late 2022 to early 2025. In September 2022, GPT-3.5 cost over $10 per million tokens. By mid-2023, those fees dropped to around $1


🧵9/n Cost declines of several technologies over time. ChatGPT’s price for a 75-word response dropped nearly to zero within its first year. Computer memory costs fell to almost zero in under two decades. Electric power costs declined more gradually, reaching roughly 2–3% of their initial price after 60–70 years. By contrast, the light bulb’s cost remained nearly flat over the same span


🧵10/n IT consumer-price index (red line) from 1989–2024. It shows compute requirements rising roughly 360% per year since around 2010—reaching 10²⁶ FLOP by 2024—while IT costs fell from an index of 100 to below 10. In other words, training power has surged as hardware has become dramatically cheaper.


🧵11/n Performance of Top AI Models on LMSYS Chatbot Arena – 1/24-2/25, per Stanford HAI


🧵12/n Share of Developers Currently Using AI in Development Processes – 2023-2024, per Stack Overflow


🧵13/n Cumulative AI-related GitHub repositories from 2015 through March 2024. Major milestones—TensorFlow (2015), the Transformers paper (2017), Hugging Face’s “hf/transformers” (2018), GPT-3 (2020), Stable Diffusion (2022), and ChatGPT launch (2022). From late 2022 to early 2024, repo count jumped roughly 175%, driven by expanding categories like infrastructure, model development, model repos, AI engineering, and applications.


🧵14/n Google Monthly Tokens Processed (T) – 5/24-5/25, per Google


🧵15/n Microsoft Azure AI Foundry Quarterly Tokens Processed (T) – Q1:24-Q1:25, per Microsoft


🧵16/n NVIDIA Quarterly Revenue by Business Line ($B) – 1/19-1/25, per NVIDIA


🧵17/n Google TPU (Tensor Processing Unit) Estimated Sales – 2021-2024, per Morgan Stanley


<a target="_blank" href="https://www.bondcap.com/reports/tai" color="blue">bondcap.com/reports/tai</a>