Nikesh Arora

All-In · Arvind Krishna & Nikesh Arora: Quantum Threat, Open vs Frontier…

• Why Will Enterprise Software Vendors Consolidate?

  Nikesh Arora says there is going to be a huge disruption in the SaaS space over the next few years. Arvind Krishna builds on that point. Krishna says the average enterprise uses anywhere from 500 to 5,000 distinct software vendors, and that stack is a massive attack surface, not only a cyber problem.

  Krishna asks whether 490 of those vendors could be replaced with minor AI capabilities, leaving 5 to 10 main platforms. The consolidation is where the spend goes. If distribution cost has to stay low and the value of each product is falling, a company cannot afford independent distribution for every vendor. Krishna says the change plays out somewhere between six months and six years.

  ▶ at 37:20 Share Transcript

• How Often Are AI-found Code Flaws Real?

  Nikesh Arora says a model that has learned what good code looks like can also point at bad code. Attackers only need one real vulnerability. Defenders have to find every one and patch it.

  When Mythos first looked for bad code, Arora says it was hallucinating 30 percent of the time. He guesses that among people who have tested those findings, roughly 60 to 80 percent have been real and 20 percent have been hallucinations. He does not think anyone will patch from a flawed suggestion without testing it again.

  ▶ at 16:41 Share Transcript

• Should Teams Use the Best AI Model First?

  Nikesh Arora says that in the experimentation phase a company should use the best model it can find, in the easiest way. He says not to restrict the team, not to cost-optimize, and not to stitch a private stack yet.

  Two teams at his company, twenty people rather than twenty thousand, have just discovered AI in the last twelve to eighteen months, and adoption is not fully diffused. Making the tools harder slows that down. Arora calls the easy-adoption stretch phase one. After that, different tasks need different models. Inspecting all traffic at an endpoint costs twenty dollars a year, or twenty to twenty-five dollars a year. Sending that traffic through a token-priced model is not practical

  ▶ at 9:33 Share Transcript

• When Could a Quantum Computer Break Today's Encryption?

  Arvind Krishna puts a working quantum computer that breaks today's cryptography at 2030. The debate he describes is 2028, 2029, or 2033, and he takes the middle of that range.

  A machine on that timeline will break today's cryptography. Krishna says the break is not a supposition. If an encrypted hard disk is stolen today, somebody could keep it for five years and break it then. Post-quantum cryptography is understood, the code is written, and he says people have been too lazy to move to it.

  DARPA's Quantum Benchmarking Initiative started with a couple of hundred companies. Krishna says about 13 are left. Some of that work is real and some of it is not quite real. The goal is a quantum comp

  ▶ at 0:35 Share Transcript

• Can AI Software Replace a Bank Lookup?

  Arvind Krishna says replacing a database lookup for retail banking, or the work of closing the books, with AI-generated software is going to be hard. He puts the reliability bar at 10 to the minus 15. The examples already on the table were interaction rich, and he treats a lookup or a close as a different case.

  Krishna says there is going to be a distinction in how easy replacement is. A digital twin would have to run for years before a cutover. All-In's reply is that there is no cost advantage to doing that.

  Interaction-rich work sits on the easier side of Krishna's distinction. Retail banking lookups and closing the books stay harder to hand to AI-generated software when the reliability

  ▶ at 39:00 Share Transcript

• Will Every State Ban Data Centers?

  Arvind Krishna says there is no chance all 50 states will ban data centers. A ban in 30 states is possible, and the remaining 20 would rub their hands in glee.

  Krishna says the regulation question on AI and data centers is driven by populism. A politician who can win more votes by looking ready to act will feel that pressure, and the pressure is real. Enough people also care deeply about the long-term economic advantage, so policy is a balancing act. Krishna says the country is on the correct balance right now, though an election can change where it falls.

  The question has been active since 2022. The Senate held closed hearings in 2022 and open hearings in 2023. Congress held hearings too,

  ▶ at 26:05 Share Transcript

• Will Agent-written Code Beat Human-written Code?

  Arvind Krishna says agent-written code will be superior to human-written code. Coding agents now write probably half the code where he works, and he says that code is already superior to what was written before.

  The advantage is evals. Agents find flaws and fix them before the code goes out. They still only catch flaws people already know how to look for, so the code is not fully verifiable. Krishna says full verification is almost computationally infeasible right now. A way to check correctness might appear when the inputs are limited. When an input can be anything, he thinks the check is really hard.

  ▶ at 20:07 Share Transcript