Amnon Shashua, Mobileye CEO: Fortt Knox Earnings
I speak with Mobileye CEO Amnon Shashua about the company's earnings and the outlook for adoption of self-driving and ...
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Search every verified Amnon Shashua interview, podcast appearance, and on-the-record quote — each transcript cross-checked by AI and human review to confirm speaker identity. Amnon Shashua, CEO and co-founder of Mobileye, has been discussing the company’s progress in autonomous driving and the broader state of AI. In earnings calls and press conferences, he stated that Mobileye’s inventory issues are behind them and that the company is experiencing over 15% year-on-year growth in chip shipments despite a slight decline in global vehicle production. He highlighted the rollout of Mobileye’s SuperVision system in China, with 300,000 vehicles already equipped, and announced design wins with Porsche and Audi for the next-generation EyeQ6 chip, expected in 2026. Shashua described Mobileye’s strategy as a hybrid approach between Waymo’s geofenced robotaxis and Tesla’s “YOLO” method, aiming for a low-cost, scalable system that uses cameras and radar rather than lidar. He noted that the company’s Chauffeur system will offer eyes-off highway driving at 130 km/h, while the robotaxi platform, based on the ID Buzz, is being tested in Munich. In academic and public lectures, Shashua has also addressed the limitations and dangers of large language models. He described current AI as a “knowledgeable idiot” that relies on massive overfitting and lacks true reasoning, though he acknowledged that machines can sample millions of attempts to improve problem-solving. He warned that adversarial prompts can trick language models and that aligning them with human values may be fundamentally difficult. Shashua predicted that regulation may eventually limit the length of human-machine conversations to prevent dangerous outcomes. He also expressed optimism that artificial general intelligence could emerge within a decade, but cautioned that the current technology is not yet capable of reaching expert-level performance in complex domains.
“I think the inventory issue has been behind us for more than two quarters already. We already have new measurements and techniques in place to make sure that this thing does not happen again — we are not relying more than just what the tier ones tell us.”
“The growth that we are experiencing right now — more than 15% year‑on‑year — is really a testament to the strength of the business even though global production is slightly decreasing; our shipment of our IQ chips are increasing.”
“There is a clear shift towards systems that move from just front‑facing camera systems to multi‑camera and radar systems — roughly a sweet spot of six cameras plus front or corner radars — and regulatory bodies are pushing the envelope on driving assist requirements.”
“We have a start of production with Audi mid‑2027 to allow 130 kilometers per hour driving, autonomous lane changing, on‑ramp/off‑ramp autonomous from highway to highway — this is a true revolution because you are buying back time.”
“Waymo's success, especially taking significant market share in ride‑hailing — about 25% of ride‑hailing in San Francisco — shows there's consumer demand for robo‑taxis even when price per mile or commute time isn't yet lower.”
“One positive thing I saw at Tesla's earnings is that the penetration rate of FSD has grown to about 25% — it means there is customer demand for these kinds of systems and they're willing to pay for it.”
“The cost of our system is very lean — cameras that don't cost much, electronics with our IQ chips maybe $1,000–$1,500, imaging radars hundreds of dollars — and the difference of another $5,000 in system cost is immaterial once you remove the driver because you're saving tens of thousands of dollars per car per year.”
“We have a very good relationship with Intel; they have been liquidating assets in a very responsible manner — the last time they sold shares was two years ago and they still have about 80% equity in the company, so I believe there will be more liquidation but done carefully.”
“GPT‑4 scored 68 on a Hungarian math matriculation exam — impressive compared to five years ago — but that score still leaves you wondering what kind of student gets 68 and whether the machine is merely overfitting to practiced problems.”
“These machines massively overfit — they overfit on the entire human knowledge — so while they look impressive in many areas, once you dig into a domain you understand deeply you find the machine is a mediocre student.”
“A reasonable description is that these machines are a 'knowledgeable idiot' — very useful assistants, but not yet transformative; you still need human supervision.”
“In autonomous driving terms current large language model technology is like Level 2 — you need constant human supervision; you cannot point and shoot and expect a verified correct solution.”
“The next frontier is building agents — imagine an AI as a member of your Slack group that receives tasks and performs them like a human — we're not there yet and it could take longer than anticipated.”
“Machines have an advantage humans don't: they can sample — try a million attempts — and that sampling, combined with good verifiers, could let us jump from mediocrity to much higher levels of problem solving.”
“Adversarial prompts are a real danger: a recent ICML paper from Hebrew University shows that no matter what you do, there can always be a long enough adversarial prompt that will trick the machine.”
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