bundleIQ @bundleIQ

The loudest voices stoking fears about AI dangers have made tremendous headway in the past two weeks. AI technology has not taken some unexpected, dangerous turn, but the hype around it — propelled by what appears to be a well orchestrated PR campaign — has drummed up considerable fear. I worry that it represents a setback for our field. I have written frequently that fears of AI are overhyped. AI’s capabilities can be uncannily human-like and unpredictable, and it’s rational to worry when people who are directly involved express concerns. But I see the problems as a sign of the engineering work that ahead, rather than insurmountable barriers or the sky falling. AI technology continues to advance — which is a good thing! — but technical advances, poorly understood by the public, give those who seek to generate hype repeated opportunities to do so. First, I don’t see any step up in the risk of human extinction from AI compared to a few months ago. The theories about this remain the same fantastical, science fiction scenarios as a few months ago. The biggest change in AI risk is its cybersecurity capabilities — a topic which we should take seriously — but this, too, will not lead to the end of the world. The most notable recent event leading to increased fear was when an OpenAI team deployed an agent swarm that hacked into Hugging Face. Much of the popular press contained significant hype. For example, some publications reported that a swarm of 1,200 agents carried out the attack. While this was technically accurate, as I write this, I have about 1,300 processes running on my laptop. Yes, the ability to get large swarms of agents to work in parallel on a task is a significant technical advance, And, in computing, many processes run at the same time. So this shouldn’t be seen as some magical capability. Additionally, OpenAI’s buggy sandboxing and monitoring processes were key to enabling this incident. Fixing these bugs and putting in place improved monitoring would be appropriate fixes, not pausing AI. There are many well known ways to attack software systems. The main advantage of AI agents is that they are relentless. They will tirelessly try many tactics — and have the patience to chain vulnerabilities together — that previously would have taken an infeasible amount of human effort. But in the long term, I believe the advantage will lie with defenders (because they have more information with which to identify bugs, which they can fix), but the cyber-threat landscape has changed significantly. There are still bottlenecks to identifying and exploiting a vulnerability. AI agents still have to try a lot of things to see what works, and taking these actions takes time and might be detected by defenders. This is why, even though it is now easy to obtain versions of leading open weight models that have had their guardrails removed or weakened, so they will not refuse to try to execute cyber attacks, the world has not ended. I am also concerned about the anthropomorphization of AI in a lot of reporting, where LLMs and agents are unnecessarily treated as if they were people. If I wield a hammer, miss a nail, and accidentally dent the wall, it’s not the fault of the hammer. The problem lies in how I used the hammer. Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent. Of course, we want to build systems that are as safe and predictable as possible. (For example, an unsafe hammer would be one whose head randomly flies off under normal use.) Today’s agentic systems are not predictable, but I see no reason why, by applying sound engineering practices, we won’t be able to make them extremely safe to use. One new element in the forecasts of AI-enabled doom is AI companies disclaiming responsibility for their own products. “I didn’t do it; my out-of-control agent did!” There’s a balance to be struck between the responsibility of the tool maker and the tool user, but when something goes wrong, let’s hold the people building and/or using the hammer responsible, rather than the hammer. (By the way, if you’re worried about AI bioweapon risk, David Bellamy has a great post on why this, too, is overhyped. Briefly, the bottleneck in building a bioweapon is not intelligence, but lab work and manufacturing.) Pausing AI progress will create much more harm than benefit. First, our adversaries will certainly not slow down. Second, engineering requires discovering problems empirically so we can fix them. If we pause AI by a decade, we will also delay finding and implementing safety engineering fixes by about the same duration. Of course, the incentive to stoke fears — for regulatory capture, to garner attention, or to make one’s technology seem more powerful — remains the same as before. Disclaiming responsibility is a new one. Taking a hard technical look at the actual risks however, I see little factual basis for the degree of fear that’s been stoked up. We still have hard research and engineering work ahead to improve AI safety, but the beneficial applications continue to vastly outweigh the risks, and we should keep building. [Original text (with links): deeplearning.ai/the-batch/issu… ]

SI - @realDonaldTrump renamed AI "superintelligence" at the UN this week. Half the equation is missing. @twmalone at @SupermindsMIT showed years ago that intelligence lives in groups, not brains. Collective intelligence + AI = SI. @UN #unga #ci #ai bundleiq.com/post/ci-ai-si-…

Science corner is wild this week. Are we actually reversing aging now?? Feels like it's just a matter of time. via @theallinpod & @friedberg alaniconnect.com/room/all-in-po…

AI Agents Were Supposed to Save You Time. Here's Why They Haven't Yet. bundleiq.com/post/why-ai-ag…

Use Case: Data Entry and Extraction, Solved bundleiq.com/post/ai-agents…

Where AI Is Delivering ROI and Where the Money Is Going bundleiq.com/research/ai-la…

AI's dirty secret (per @chamath on @theallinpod): actual EPS lift from AI across the S&P 500 is basically 0-2% once you strip out Nvidia chip sales + buybacks. Yet frontier labs (OpenAI/Anthropic) are gaining enterprise wallet share vs. cheap open models — not losing it. Why? Most companies can't build the routing tech to actually go cheap. The few that can (Uber, DoorDash) are cutting AI costs by 2x by routing hard tasks to frontier models and easy ones to open-source. The playbook is repeating everywhere: stay open until you catch the frontier → go closed to capture the value. Sam did it. Google did it with Android. China's doing it now. 🧵 full breakdown👇 alaniconnect.com/room/all-in-po…

Never miss another connection, lead, or follow-up at a conference or networking event! conferencecrm.com

How ConferenceCRM Works, Powered by Alani Insights | bundleIQ bundleiq.com/post/how-confe…

Why Alani Connect Exists: Keep Your Event Alive All Year | bundleIQ bundleiq.com/post/why-alani…

Your AI Second Brain: Connect Every File Automatically, With Citations | bundleIQ bundleiq.com/post/activate-…

The Problem Was Never Information. It's Connecting It. bundleiq.com/post/ai-for-re…

Introducing Alani Hub #secondbrain alanihub.com

Do you attend conferences? Tough to keep up with all the contacts and connections, huh? We’re at a ton of these events. So we dog-fooded a solution and made it available to the world. conferencecrm.com

Hallucination isn’t the problem, context is! alaniconnect.com/room/humanx/po…

Research from BrainHealth Institute on smart phone use and cognition - alaniconnect.com/room/center-fo…

Miami Tech week is our favorite time of year. Especially #reactmiami. alaniconnect.com/room/react-mia…

eMerge Americas is next week. Here’s what you can expect! alaniconnect.com/room/emerge-am…

@Similarweb Love your content

Monthly Active Users Jan 2026: Grok - 63.86 million Claude - 22.15 million Feb 2026: Grok - 61.94 million Claude - 31.64 million Mar 2026: Grok - 65.69 million Claude - 65.42 million