bwfan123

> CS is going to be the first field to be "solved."

With due respect, your statement reflects a lack of experience building production software. In real-world software systems, code is only one aspect. Automation helps, but "what needs to be built" is a harder problem and remains a human endeavor.

Disagree only because I think LLMs write more coherently. It had to be written by a human since it read like unadulterated doodoo. Nothing in the article can be tested for truth-value. A bunch of metaphors are invoked. Sentences like these make no sense to me.

> The returns on attention rise, and with them the incentive to pay attention.

> We might call this a cognitive industrious revolution, preceding and perhaps enabling a fuller AI industrial revolution

Anthropic is expected to spend 500B of money it doesnt have. Based on these commitments, data-centers have ordered equipment which includes memory. So, a lot of demand for memory is built on a speculative foundation.

> They want regulation around AI

So, there is a regulatory framework for "safe-ai" that shields these companies from liability. This way, they can sell "safe-ai" to enterprises and if shit-hits-the-fan at the enterprise, sorry, this is certified "safe-ai" so, your bad. Shift blame. From an enterprise buyer's perspective they can say, hey, I bought "safe-ai" and so dont fire me when it "rm -rf"s the production database. Still, it beats me why they are painting their product in a negative light, and scaring their own enterprise customers. After this sort of marketing, any enterprise buyer would be scared to go anywhere near it

> Is that the fault of AI or management for not firing them?

How does the system behave in a variety of scenarios including failures and restarts. How is state maintained coherently. There are the kinds of systems problems that an engineer needs to reason through, and if there are bugs in such decisions, they end up becoming costly. I dont expect AI or LLMs to solve these problems at all, since each of them has nuances and tradeoffs which are specific to each system. In short, there is specification complexity in precisely describing system wide behaviors, and unfortunately, there is no lean/tla+ to meaningfully describe systems at scale. You could then ask: How can a system have guaranteed behaviors if they cannot be even stated or proved formally ? The answer to this is how protocols like raft/paxos initially convinced us of their behaviors which is in human review and understanding. That begs the question: How can human review and understanding be reliable, and the answer is that it is not reliable, but humans have ability and processes to continuously learn from experience in the real world. So, our understanding is grounded not only by whats out there in books etc, but also by our own interactions with the world.

Long story short: The responsibility for system-wide behaviors of software systems relies on human review and understanding, which while imperfect can continuously learn.

At a startup I worked, there was an engineer whose code was incoherent and buggy. So, we were literally better off if that engineer did nothing because their net output was negative. Engineers like that become weaponized with LLMs, and negative numbers become larger negative numbers when scaled up.

> The ai threat is real ridiculous

It is an elaborate business ploy to create a regulatory framework for "safe-ai" that shields these companies from liability. This way, they can sell "safe-ai" to enterprises and if shit-hits-the-fan at the enterprise, sorry, this is certified "safe-ai" so, your bad. Shift blame to a regulatory body. From an enterprise buyer's perspective they can say, hey, I bought "safe-ai" and so dont fire me when it "rm -rfs" the production database. Still, beats me why they are painting their product in a negative light, and scaring their own enterprise customers. After this sort of marketing, any enterprise buyer would be scared to go anywhere near it.

> Oracle was ever going to be a major player in AI

Stupidity on the behalf of management to get into AI at any cost even if it means becoming a land-lord of AI data-centers. They have good company with allbirds and other crypto-miner-turned datacenter operators. This is what a mania looks like. Hustlers of all shapes and sizes line up for dumb money which wont ask any questions. At the backend of this, these operators will be cleaned out, and sold to the highest bidders and that explains why microsoft is renting capacity, because they know at some point in the future there will be foreclosures, and they can buy on the cheap.

I am running it on M3 pro. Works great except for prefill speed which makes it slow for many coding tasks. The newer generation of macs are promising but as a cost-sensitive user, I am also looking into cheaper 32 GB gpus from intel, AMD, nvidia. Eventually, I think these class of models will work well for most coding usecases especially given that I certainly want to have some control of the code generated.

> exfiltrating the entire content of the system

Since the contents of every session is owned by the user including the outputs, I am curious if the user now owns all the files given to them.