Chinese stuff you can find it cheaper elsewhere most of the time. For the rest, amazon is still cheaper, faster to deliver and easier to return

More specifically, the CPU cores in AWS Graviton5 are Neoverse V3 cores, which implement the Armv9.2-A ISA specification.

Neoverse V3 is the server version of the Cortex-X4 core which has been used in a large number of smartphones.

The Neoverse V3 and Cortex-X4 cores are very similar in size and performance with the Intel E-cores Skymont and Darkmont (the E-cores of Arrow Lake and of the future Panther Lake).

Intel will launch next year a server CPU with Darkmont cores (Clearwater Forest), which will have cores similar to this AWS Graviton5, but for now Intel only has the Sierra Forest server CPUs with E-cores (belonging to the Xeon 6 series), which use much weaker CPU cores than those of the new Graviton5 (i.e. cores equivalent with the Crestmont E-cores of the old Meteor Lake).

AMD Zen 5 CPUs are significantly better for computationally-intensive workloads, but for general-purpose applications without great computational demands the cores of Graviton5 and also Intel Skymont/Darkmont have greater performance per die area and power consumption, therefore lower cost.

Honestly this benchmark feels completely dominated by the instance's NIC capacity.

They used a c5.4xlarge that has peak 10Gbps bandwidth, which at a constant 100% saturation would take in the ballpark of 9 minutes to load those 650GB from S3, making those 9 minutes your best case scenario for pulling the data (without even considering writing it back!)

Minute differences in how these query engines schedule IO would have drastic effects in the benchmark outcomes, and I doubt the query engine itself was constantly fed during this workload, especially when evaluating DuckDB and Polars.

The irony of workloads like this is that it might be cheaper to pay for a gigantic instance to run the query and finish it quicker, than to pay for a cheaper instance taking several times longer.

All things people used to own 10 years ago. It’s not like the people doing that stuff have vanished.

Cloud’s big promise was speed to market and price, and let’s be honest, price is no longer there compared to a decent operation.

The one thing where clouds remain kings is speed for small teams. Any large enough company should probably Ask themselves whether running their own operation using ias would be a better choice.

Grok? Next…

One wonders how exactly this will be enforced.

I've used ChatGPT to help understand medical records too. It's definitely faster than searching everything on my own, but whether the information is reliable still depends on personal judgment or asking a real doctor. More people are treating it like a doctor or lawyer now, and the more it's used that way, the higher the chance something goes wrong. OpenAI is clearly drawing a line here. You're free to ask questions, but it shouldn't be treated as professional advice, especially when making decisions for others.

I might be in the minority here but I've consistently found Gemini to be better than ChatGPT, Claude and Deepseek (I get access to all of the pro models through work)

Maybe it's just the kind of work I'm doing, a lot of web development with html/scss, and Google has crawled the internet so they have more data to work with.

I reckon different models are better at different kinds of work, but Gemini is pretty excellent at UI/UX web development, in my experience

Very excited to see what 3.0 is like