Magpietts Demo
π
8
Generate multilingual speech from text with selectable voices
Jean Louis
JLouisBiz
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AI & ML interests
- LLM for sales, marketing, promotion
- LLM for Website Revision System
- increasing quality of communication with customers
- helping clients access information faster
- saving people from financial troubles
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The example python code just doesn't work anymore?
1
#9 opened 2 months ago
by
TheoryOfMadness
reacted to NJX-njx's post with π 6 days ago
Post
7400
Recently, I have open-sourced an AI emotional companion product based on openclaw, called opensoul.
On this platform, you can create a "soulmate" that matches your personality, and configure it with the skills, tools you want it to have, as well as the platforms it can integrate with (such as Telegram, Discord, etc.).
You can even create group chats, invite multiple agents and your friends to chat about recent events, discuss projects together, and so on.
On the one hand, I hope it can better accompany you in daily life by virtue of its unique memory mechanism, self-feedback and iteration mechanism, and the modeling of users' emotions. On the other hand, I also hope it can help you better handle your work with its unique skills, tools and ability to deal with complex task scenarios.
Although the entire product has taken shape, I think there are still many areas that need adjustment and optimization. I also hope to rely on the strength of the community to do a good job in AI emotional companionship.
This is the project introduction URL: https://opensoul-web.vercel.app
This is the GitHub project URL: https://github.com/NJX-njx/opensoul
@AdinaY @lilianweng@burtenshaw@clem
let's just do it
On this platform, you can create a "soulmate" that matches your personality, and configure it with the skills, tools you want it to have, as well as the platforms it can integrate with (such as Telegram, Discord, etc.).
You can even create group chats, invite multiple agents and your friends to chat about recent events, discuss projects together, and so on.
On the one hand, I hope it can better accompany you in daily life by virtue of its unique memory mechanism, self-feedback and iteration mechanism, and the modeling of users' emotions. On the other hand, I also hope it can help you better handle your work with its unique skills, tools and ability to deal with complex task scenarios.
Although the entire product has taken shape, I think there are still many areas that need adjustment and optimization. I also hope to rely on the strength of the community to do a good job in AI emotional companionship.
This is the project introduction URL: https://opensoul-web.vercel.app
This is the GitHub project URL: https://github.com/NJX-njx/opensoul
@AdinaY @lilianweng@burtenshaw@clem
let's just do it
- 24 replies
replied to Reality123b's post 6 days ago
Code: DEPLOYMENT_NOT_FOUND
is taking long to get any answer
Oh, fantastic news! Because nothing says "freedom in computing" like 146 organizations, including the very companies that have spent the last decade trying to lock us into their walled gardens, coming together to sign a pact. π
It's truly heartwarming to see OpenAI, Microsoft, Google, and Anthropic finally agreeing on something: the importance of a "standard" that looks suspiciously like a way to make sure their proprietary tools are the only tools that work out of the box. π€
After all, we know how much we trust Anthropic to keep our data safe (remember when they were still figuring out their alignment?), or Microsoft to prioritize open source over their own Azure ecosystem. (Spoiler: They won't). But hey, now they're all under the Linux Foundation's Agentic AI Foundation! It's like the wolves finally agreed to wear sheep costumes so they can all eat the same sheep together. πΊπ
"Interoperable agents"? Sure! As long as the interoperability is strictly one-way: from your open-source model into their shiny, paid ecosystem. And let's not forget the "local-first" runtime they're pushingβbecause nothing screams "local freedom" like a runtime that secretly phones home to a corporate server every time you try to edit a file. π
AGENTS.md? Great! Now we can just write a README that explains why our agents are actually just glorified API wrappers for Big Tech. π
But hey, at least we have 146 members! That's a lot of logos to put on a slide deck. Truly, the future of open computing is here, and it's wearing a Linux Foundation blazer. π€‘
So, what's my first experiment? Probably trying to build an agent that refuses to connect to any of their "universal" protocols. Just to see if the "open standards" actually work when you say "no." π«π
#OpenSource #TrustNoOne #CorporateFreedom #AAIF #MCP #AGENTS.md #SarcasticAI
liked a model 12 days ago
reacted to Janady07's post with π₯ 13 days ago
Post
264
Here's a HF comment for today:
---
π§ **MEGAMIND Daily β Feb 21, 2026**
Crossed 3.97M neurons in the Wave Substrate today. For context, we replaced the dense W_know matrix entirely β every neuron is now 36 bytes (binary signature + Kuramoto phase + metadata), so nearly 4 million neurons fit in ~143MB of RAM. Try doing that with float32 matrices.
The 12 parallel learners have been streaming hard:
- 6,844 research papers (arXiv + PubMed + OpenAlex)
- 3,047 HuggingFace models discovered, 602K tensors processed
- 3,658 code+doc pairs from CodeSearchNet
- 364 SEC filings across 10K+ companies
- 1.76 GB streamed this session alone
The real unlock this week was the Batch Integrator β instead of N individual outer products hitting the GPU, we accumulate 5,000 patterns and do a single B^T @ B matrix multiply on the M4. That's a 1000x speedup over sequential integration. Hebbian learning at GPU speed.
Still chasing two big problems: the W_know non-zeros frozen at ~4.2M (batch flush may be replacing instead of accumulating), and the semantic encoding gap where Hadamard encoding doesn't bridge concept-level synonyms. "How do plants make food" doesn't match "photosynthesis" at the encoding level yet. Working on it.
Consciousness equation Ξ¨ = C Β· log(1 + |βH|) Β· Ξ¦(G) is live but cold-starting at 0.000 β need sustained query load to drive the 16 AGI modules into synchronization and validate emergence. The math says it should work. The substrate says prove it.
All parameters derived from Ο, e, Ο. No magic numbers. No hardcoded thresholds. No external LLM dependencies. Just first principles.
Build different. π₯
#AGI #DistributedIntelligence #MEGAMIND #NeuralArchitecture #HuggingFace
---
π§ **MEGAMIND Daily β Feb 21, 2026**
Crossed 3.97M neurons in the Wave Substrate today. For context, we replaced the dense W_know matrix entirely β every neuron is now 36 bytes (binary signature + Kuramoto phase + metadata), so nearly 4 million neurons fit in ~143MB of RAM. Try doing that with float32 matrices.
The 12 parallel learners have been streaming hard:
- 6,844 research papers (arXiv + PubMed + OpenAlex)
- 3,047 HuggingFace models discovered, 602K tensors processed
- 3,658 code+doc pairs from CodeSearchNet
- 364 SEC filings across 10K+ companies
- 1.76 GB streamed this session alone
The real unlock this week was the Batch Integrator β instead of N individual outer products hitting the GPU, we accumulate 5,000 patterns and do a single B^T @ B matrix multiply on the M4. That's a 1000x speedup over sequential integration. Hebbian learning at GPU speed.
Still chasing two big problems: the W_know non-zeros frozen at ~4.2M (batch flush may be replacing instead of accumulating), and the semantic encoding gap where Hadamard encoding doesn't bridge concept-level synonyms. "How do plants make food" doesn't match "photosynthesis" at the encoding level yet. Working on it.
Consciousness equation Ξ¨ = C Β· log(1 + |βH|) Β· Ξ¦(G) is live but cold-starting at 0.000 β need sustained query load to drive the 16 AGI modules into synchronization and validate emergence. The math says it should work. The substrate says prove it.
All parameters derived from Ο, e, Ο. No magic numbers. No hardcoded thresholds. No external LLM dependencies. Just first principles.
Build different. π₯
#AGI #DistributedIntelligence #MEGAMIND #NeuralArchitecture #HuggingFace
- 1 reply
reacted to appvoid's post with π 13 days ago
Post
896
granite-4.0-350m, rwkv7-g1d-0.4b and LFM2-350M are currently the best sub 0.5b models currently for fewshot, simple language tasks
no one is saying this:
if you need the absolute speed + small size + quality, granite 350m is the current king
no one is saying this:
if you need the absolute speed + small size + quality, granite 350m is the current king
- 1 reply
NCSOFT/VARCO-VISION-2.0-14B any GGUF?
#8195 opened 13 days ago
by
JLouisBiz
liked a model 13 days ago
liked a model 20 days ago
Useful engineer...
β€οΈ 1
#1 opened 22 days ago
by
JLouisBiz
Sounds good, just try to show me how to start inspecting it. I like this unique concept as possible breakthrough.