i am still working on easyanalytica tool to auto generate dashboards without ai .
I recently added comparison feature and figuring that out was fun. There are lot of interesting ideas on execution side of it but for end user its a simple product, just give data and see the dashboard.
html snippet playground - for testing html/react snippets
token speed calculator - for estimating tg/s of ai based on ram speed and model size/params this helps in comparing different hw, estimating likely speeds i will get on hardware
prompt assembler - to create prompt and context once and reuse it in different ai's, picking and choosing context in a prompt, creating agent.md etc.
dashboard builder - for viewing gsc, ga, stripe data in one place
This is market introductory pricing that hasn't factored in cost recovery. Most of it has been run on early investment with the assumption they will recover costs in the long run. The prices are subsidized across the board and they will need to go up signficantly to recover them.
Assuming this were accurate, then presumably the AI companies would be betting that inference costs come down before the bill is due - I don't see enterprises being willing to absorb another ~10x price increase for tokens (as they've just done going from subscription prices to per-token pricing)
For claude shops this was a huge hit. But lets back this up. There are some companies that haven't even built a break-even model at this price because they are funded by investment. As soon as those investors lose patience the first dominos will fall. For those who have somewhat of a business model, will it survive a price increase? The bigger question is do the base model providers have enough runway and have a way to keep going as they need to recover costs.
Aren’t the Chinese labs quickly turning them into a commodity?
The open-weight models will have a steady race to the bottom on inference costs just by dint of competition between providers. They aren’t at the frontier yet, but they are rapidly eating the flash market.
Yeah, that's not going to work if you can get e.g. 80% of value by using 10-20x or more cheaper open models. At some point it would just make sense for large companies to rent compute and deploy their version of DeepSeek or whatever (if they don't trust Chinese providers)
i use smaller model gemma e2b for most of my editing and it works surprisingly well. Workflow is planning with sota models and execution via small models. If you plan properly dont leave ambiguity for smaller model it works well.
Out of curiosity have you tried other small models? The e2b for me was unusable. Llama3.2 3b was better and that thing is a year old and I rarely use it now too.
yes i keep on trying small models, i have also tried qwen 3.5 0.8B, 2B, 4b and gemma4 e4B models but they either did not worked reliably (thinking loop, issue in following instruction) or there were performance issues (prompt speed, tg speed, too much ram) e2b was the sweet spot where i could give it plan and it can edit files properly.
why do people want to continue to use anthropic despite their shitty service? its not like they have some kind of lock-in as it is still new company and it has shown its color before we are stuck with it unlike google/meta etc.
Totally agree. This is why open source models and toolings are so important for the ecosystem. I would not want these companies decide what we can or cannot do.
I did a showhn with similar idea(got a whooping 1 point and was flagged as spam which was later removed by mods), you paste your html and it encodes it into url, you can share the url without server involvement. I even added a url shortener because while technically feasible encoded url becomes long and QR code no longer works reliably. I also added annotation so you can add your comments and pass it to colleagues.
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