this is a great video to watch if you're curious about how the bloomberg terminal ui was made. https://youtu.be/ODgs0eWAIKc
32 karma · joined July 13, 2016
software tourist.
this is a great video to watch if you're curious about how the bloomberg terminal ui was made. https://youtu.be/ODgs0eWAIKc
Configure Thelio Mira with up to:
16-core AMD Ryzen 9000 Series CPU
192 GB DDR5 RAM
Dual NVIDIA RTX Pro 6000 GPU
192 GB GPU memory
this is miss leading. actually it is 4gb ram a400 price.dual RTX6000 price is : $40,538.00
But the right move is to find a way to increase the rate at which you generate ideas and offload the coding almost entirely to AI. Because if you’re not doing that, someone else is. They’ll eventually build something better than your app.
And when people stop choosing your product, if you can’t come up with the next idea and this is your only source of income... well, good luck.
https://openai.com/index/hugging-face-incident-and-the-road-...
This account was created only 13 days ago.
It has made only one submission, which is this post, and had only two comments before submitting it.
How does this happen?
I have an HN account that is 10 years old, but when I submit something, it often gets flagged almost immediately. So how exactly does HN’s flagging and ranking system work? Does account age or karma matter at all?
For reference:
user: terranivium created: 13 days ago karma: 18 about: vocalslice.com
eventually, they fell back to rust.
there's a lesson here: subset languages are fine for experiments and small projects, but they're rarely the right choice for production software.
...and C still can't be replaced. it's still the language of choice for mission-critical systems and low-level problem solving.
https://developer.nvidia.com/blog/train-small-orchestration-...
"Ultimately, if more companies treated the framework as an extension of the application, it would result in higher resilience and stability. Investment in Rails ensures your foundation will not crumble under the weight of your application. Treating it as an unimportant part of your application is a mistake and many, many leaders make this mistake." https://github.blog/engineering/architecture-optimization/bu...
bitflippin...
And i dont know why you wanted me to give you all my permissions?
This project violates Claude Code's Terms of Service by automating Claude to create an unattended chatbot service that responds to third-party messaging platforms (WhatsApp, and what you add ...).
The exact issues:
1. Automated, unattended usage - The system runs as a background service (launchd) that automatically responds to WhatsApp
messages without human intervention (src/index.ts:549-574)
2. Building a bot service - This creates a persistent bot that monitors messages and responds automatically, which violates restrictions on building derivative services on top of Claude
3. Third-party platform integration - Connecting Claude to WhatsApp (or other messaging platforms) to create an automated
assistant service isn't an authorized use case.
The README itself reveals awareness of this issue at line 41:
**No ToS gray areas.** Because it uses Claude Agent SDK natively with no hacks or workarounds, using your subscription with your auth token is completely legitimate (I think). No risk of being shut down for terms of service violations
(I am not a lawyer).
The defensive tone ("I think", "I am not a lawyer") indicates uncertainty about legitimacy. While using your own credentials doesn't automatically make automated bot services compliant—Anthropic's TOS restricts using their products to build automated chatbot services, regardless of authentication method.
The core violation: transforming Claude Code into an automated bot service that operates without human intervention, which is explicitly prohibited.What's included:
- 19 always-on models with both UI and API access
- LoRA fine-tuning support (FP8 precision, up to rank-64)
- Embedding models at no extra cost
- Standard: $20/month (135 msgs/5hrs), Pro: $60/month (1,350 msgs/5hrs)
Technical specs:
- Always-on models: No quantization (full precision)
- On-demand models: BF16 precision (FP8 for Jamba-based models only)
- LoRAs: FP8 precision, rank-8 to rank-64 support
- On-demand GPU pricing: 80GB at 3¢/min, 48GB at 1.5¢/min, 24GB at 1.2¢/min
- On-demand context limit: 32k tokens
Complete always-on model list:
DeepSeek: R1, R1-0528, V3, V3-0324, V3.1 (all 128k)
Meta Llama: 3.1-405B/70B/8B, 3.3-70B (128k), 4-Maverick-17B (524k), 4-Scout-17B (328k)
Others: Kimi-K2 (128k/256k), GPT-OSS-120B (128k), Qwen2.5-Coder-32B (32k), Qwen3-235B variants (256k), Qwen3-Coder-480B (256k), GLM-4.5 (128k)
Additional features:
- LoRA support for Llama 3.1/3.2 base models
- Embedding model: nomic-ai/nomic-embed-text-v1.5
- Any HuggingFace model available on-demand
Links: https://synthetic.new/ | With referral: https://synthetic.new/?referral=9oxapskWLeOrDT5
https://www.youtube.com/watch?v=LE8HiHZcgEE https://www.youtube.com/watch?v=ODgs0eWAIKc