mectors

Greentic.ai is an open-source platform to create and run digital workers—autonomous bots that call APIs, tools, and plugins. Define workflows in YAML, and the Rust/WASM-based engine handles execution. Supports messaging channels (Telegram, Slack, etc.), custom MCP tools, and dynamic flows. Think Zapier/NodeRed meets AI agents, but fully programmable and privacy-friendly.

v0.2.0 out now. Local-first. Cloud + oAuth coming soon. https://greentic.ai

What are the advantages and disadvantages of both and where are both still missing capabilities.

Python Docker images with CUDA, Python, Pytorch,... are 5GB to 10GB of third-party code. Here is an example of bringing this down to 1.13GB thanks to WasmEdge, 10MB of LlamaEdge API Server [compatible with ChatGPT] and 1.17GB for TinyLlama.

The lack of differentiation between two EV brands will not be the major disruption to the car industry. It will be the ownership. In 3 to 5 years we should see autonomous vehicles that are offered by robot taxi networks. The same car can offer transport services to 5 families or more and still each family will be able to use the car to similar levels they are currently used to. Customers will no longer have to worry about maintenance, charging, insurance, parking, cleaning,... They will pay less and get more. The outcome will be that the number of cars sold will be a lot less than today. Car companies will not be able to make any margin on maintenance because EVs need a lot less maintenance and can soon drive a million kilometres. Only very few companies can create/train the self-driving technology, e.g. Tesla, Google,... The outcome will be that we will see a lot less car companies.

A simple suggestion: Have a mobile optimised version of the website.

At Legal and General we use hyperleder to power Estuare, the first pension risk transfer reinsurance in production. Our reinsurer is based in Bermuda and given the population is only 64K and has very few unemployed actuaries, it is hard to scale the reinsurance business via hiring people. Thanks to Estuare monthly operations related to high value contracts with insurers can be fully automated and allow the business to scale. Given that the insurer and reinsurer can both introduce new data and eiter sides used to do extremely complex calculations in a spreadsheet to validate how much money needs to flow in which direction each month, the process would take weeks due to often human error. With Estuare the process now takes minutes and is fully auditable, which for contracts that can run 50 years is important, as well as allowing previous data updates to be incorporated immediately instead of once a year.

Windows, usability is worse than MacOS, installing software is more complex than Android and iOS, code is worse than any flavor of Linux but still somehow it is default for most people with a 9x5 job.

Some criteria: Bread of services, innovations, ecosystem: AWS Microsoft technology focus,ease of use: Azure Fast global networking, Kubernetes, Tensorflow: GCE Cheap servers: challengers Niche: ARM servers - Scaleway, ...

Yes, by default 4 times a day the OS looks if there are updates. Manually you can do snap refresh as well. If an update fails you can rollback transactionally.

I speak 5 languages. In 4 I gave conference speeches, had job interviews and participated in work discussions. The last one I never managed to master to the same level for as much books I read or lessons I would follow. The difference, I never was for a prolonged time in a place where I had no choice but to learn the language.

LXD will be another Snappy Framework, just like Docker...