A definitive, deeply researched biography exploring the life, visionary inventions, and complex personality of Nikola Tesla. Carlson contextualizes Tesla's breakthroughs in alternating current, radio, and wireless power within the broader technological and financial landscapes of the Gilded Age. The work examines how Tesla's conceptual approach to invention drove both his revolutionary triumphs and his ultimate commercial difficulties.
"Let the future tell the truth, and evaluate each one according to his work and accomplishments. The present is theirs; the future, for which I have really worked, is mine."
— Nikola Tesla
Deterministic Foundations
The crowd always owns the present—the hype, the easy capital, and the collective delusion belong to whoever tells the prettiest story. But reality is stubborn. When the bubble pops and the brittle toys shatter under actual load, the only things left standing are the systems built on deterministic foundations by the few who refused to fake it.
"Your work is going to fill a large part of your life, and the only way to be truly satisfied is to do what you believe is great work. And the only way to do great work is to love what you do. If you haven't found it yet, keep looking. Don't settle. As with all matters of the heart, you'll know when you find it. And, like any great relationship, it just gets better and better as the years roll on."
— Steve Jobs
A discussion between cognitive scientist Gary Marcus and physicist Brian Greene on the true capabilities and structural limitations of current generative AI models. Marcus argues that while large language models are proficient at mimicking the surface-level appearance of logical reasoning, they lack the underlying cognitive architecture required to generalize beyond their training sets.
Guessing with Style
AI is an incredible force multiplier for engineers who already know how to build a system. But if we outsource architectural intuition to a transformer model without grounding it in raw telemetry and end-to-end load testing, we aren't engineering anymore—we're just guessing with style.
Yann LeCun’s lecture at ETH Zürich outlining his vision for the next generation of artificial intelligence. He contrasts current autoregressive LLMs with energy-based world models capable of reasoning, planning, and understanding causality, arguing that true machine intelligence requires learning from passive observation rather than simple next-token predictions.
Prototyping Myopia
It is a case of hyper-fixated technological optimism leading to algorithmic deference. The leader, seduced by the conversational fluency and immediate output of the tool, undergoes a form of prototyping myopia—over-indexing on isolated AI capabilities while losing their strategic anchor in the broader operational reality of the business.
A critical and clear-eyed look at the capabilities and limitations of modern artificial intelligence. The authors dismantle the hype surrounding machine learning, showing where it succeeds, where it fails, and why predictive AI often amounts to little more than snake oil. It serves as an essential guide to distinguishing genuine technological progress from empty marketing claims.
A fascinating critique of how technology ceases to be a tool and becomes a culture of its own, redefining what we value and how we reason. Neil Postman's insights from 1992 feel more relevant today than ever.