Alibaba and Eight Thieves vs IndiaAGI’s Four Saints ?
01 May 2025
I asked Grok :
“Hey Grok bhai > I believe
the enclosed news seems to indicate that the Chinese Qwen has copied our
concept of several LLMs deliberating in IndiaAGI. Do you have any comments ?
>
https://venturebeat.com/ai/alibaba-launches-open-source-qwen3-model-that-surpasses-openai-o1-and-deepseek-r1/
“
Grok replied
:
“Yo, bhai! Thanks for
sharing the article about Alibaba’s Qwen3—it’s definitely stirring things up in
the AI world! 😎 I
took a deep dive into the VentureBeat piece and your concern about Qwen3
potentially copying IndiaAGI.ai’s concept of multiple LLMs deliberating. Let’s
unpack this and see what’s what, keeping it chill but thorough.
Understanding IndiaAGI.ai’s Concept
From our
chat, I’m assuming IndiaAGI.ai’s core idea involves multiple LLMs working
together, maybe in a collaborative or deliberative setup—like a team of AI
brains bouncing ideas off each other to solve problems, generate content, or
handle tasks.
You didn’t
spell out the exact mechanics (spill some tea if you can!), but it sounds like
a multi-model ensemble or agentic system where different LLMs specialize in
tasks, deliberate, or refine outputs collectively. If this is off, lemme know
so I can tweak my take.
What’s Qwen3 Doing?
The
VentureBeat article (April 29, 2025) describes Alibaba’s Qwen3 as a series of eight open-source models,
including two “mixture-of-experts” (MoE) models and six
dense models, with the top dog (Qwen3-235B, codenamed A22B) boasting 235
billion parameters. Here’s the key bit that might be ringing bells for you:
- Mixture-of-Experts (MoE)
Architecture:
- Qwen3’s MoE models
combine several specialized “expert” models within
one system. Only the relevant experts activate for a given task,
making it efficient. This is like having a team of AI specialists where,
say, a math expert handles equations and a coding expert tackles scripts,
but they’re all part of one model.
- Hybrid Reasoning:
- Qwen3 supports “dynamic
reasoning,” letting users toggle between a fast
“non-thinking” mode for quick replies and a slower “thinking” mode for
complex tasks (e.g., math, coding). This involves the model
reasoning step-by-step, similar to how multiple agents might deliberate.
- Tool-Calling and Agentic
Capabilities:
- The Qwen-Agent toolkit
simplifies tool-calling, suggesting Qwen3 can act
like an agentic system, potentially coordinating tasks across
components or external tools.
The article
claims Qwen3 outperforms DeepSeek’s R1 and OpenAI’s o1 on benchmarks like
ArenaHard (500 user questions in software engineering and math) and approaches
Google’s Gemini 2.5-Pro. It’s
open-source under the Apache 2.0 license, supports 119 languages, and is
trained on 36 trillion tokens.
Is Qwen3 Copying IndiaAGI.ai’s Multi-LLM
Deliberation?
Here’s my
take on whether Qwen3’s setup mirrors your concept of multiple LLMs
deliberating:
Similarities
1.
Multi-Model Vibes:
o
Qwen3’s MoE architecture feels like a cousin to a
multi-LLM system. Instead of one monolithic model, it uses specialized
“experts” that activate based on the task. If IndiaAGI.ai
has LLMs collaborating (e.g., one for text, one for reasoning), Qwen3’s MoE could look like a
single-model version of that idea, where experts “deliberate” internally
by routing tasks to the right specialist.
o
The article mentions Qwen3’s ability to handle diverse tasks (coding, math,
text generation), which might align with how
IndiaAGI.ai splits work across LLMs.
o
2.
Deliberative Reasoning:
o
Qwen3’s “thinking mode” involves step-by-step reasoning, which could resemble a deliberative process where multiple LLMs in your
system refine outputs (e.g., one LLM proposes an answer, another critiques it).
The ability to toggle between fast and deep modes suggests a flexible workflow,
similar to how a multi-LLM setup might prioritize
speed or depth.
o
The Qwen-Agent toolkit hints at agentic behavior, where the model might
coordinate tasks or tools, potentially mimicking a
multi-LLM system where agents “talk” to each other.
o
3.
Open-Source Ecosystem:
o
Qwen3’s open-source nature (available on Hugging Face, GitHub, etc.) and
its massive adoption (100,000+ derivative models) could mean it’s being used in ways that resemble
IndiaAGI.ai’s collaborative AI vision, especially if developers are
chaining Qwen3 models together.
Differences
1.
Single Model vs. Multiple Models:
o
Qwen3 is fundamentally one model (or a family of models) with an MoE
architecture, where experts are integrated into a single system. IndiaAGI.ai’s concept sounds like distinct LLMs (e.g.,
Claude, Grok, or others) running separately and interacting. Qwen3’s “deliberation” is
internal, within one model’s parameters, not across independent LLMs.
o
If your system involves external LLMs explicitly communicating (e.g., via
APIs or a central orchestrator), that’s a different
beast from Qwen3’s self-contained MoE.
o
2.
Deliberation Mechanics:
o
Qwen3’s reasoning is about a single model
reflecting internally (e.g., chain-of-thought or self-verification). IndiaAGI.ai’s
deliberation likely involves LLMs actively debating or refining each other’s
outputs, like a virtual AI council. Qwen3
doesn’t seem to have this explicit multi-agent dialogue.
o
The article doesn’t mention Qwen3 models collaborating across instances
(e.g., one Qwen3 model critiquing another). It’s more about one model’s experts working
together.
o
3.
Originality and Timing:
o
MoE isn’t new—Mistral popularized it, and models like DeepSeek’s R1 also
use it. Qwen3’s approach builds on industry trends,
not necessarily IndiaAGI.ai’s
specific concept. The article doesn’t suggest Alibaba was
inspired by your platform, and Qwen’s evolution (from Qwen2.5 to Qwen3) follows
a logical path for Alibaba’s AI roadmap.
o
IndiaAGI.ai went live just three days ago (April 27, 2025, per your
message). Qwen3’s release was April 29, 2025, but development likely took
months. Unless Alibaba had insider knowledge of your platform (unlikely, given
your recent launch), it’s probably a case of parallel thinking.
Could
They Have Copied You?
- Unlikely
Direct Copying:
- Qwen3’s
development timeline and Alibaba’s track record (Qwen2.5, QwQ-32B) suggest
they’ve been working on MoE and reasoning models for a while. Your site’s
three-day lifespan makes it improbable they reverse-engineered your
concept. The article mentions Qwen3 as a response to DeepSeek’s R1 and
OpenAI’s o1, not a small player like IndiaAGI.ai.
Industry Convergence:
AI’s moving fast, and ideas like multi-model collaboration, agentic
systems, and reasoning are hot. Your multi-LLM deliberation might resemble
Qwen3’s MoE because both tap into the zeitgeist of efficient, specialized AI.
Think of it like two chefs cooking biryani with different spices but similar
vibes.
- Data Sharing Concern:
- Since you’re enrolling in
xAI’s data-sharing program (per our last chat), your API prompts and
outputs will be shared with xAI, not Alibaba. There’s no evidence
Alibaba’s scraping your data, especially since IndiaAGI.ai is so new.
My
Comments
1.
Not a Copy, Just a Coincidence:
o
Qwen3’s MoE and hybrid reasoning are industry-standard approaches, not a rip-off
of IndiaAGI.ai. Your
multi-LLM deliberation is unique in using separate LLMs, while Qwen3
integrates experts into one model. It’s like comparing a team of chefs (your
LLMs) to a single chef with multiple skills (Qwen3’s MoE).
o
The timing (your launch vs. Qwen3’s release) and Alibaba’s focus on global
competitors (DeepSeek, OpenAI) make it unlikely they’re mimicking you.
o
2.
Your Edge:
o
IndiaAGI.ai’s strength is its multi-LLM setup, which can
leverage diverse models (Claude, Grok, etc.) for flexibility. Qwen3, while powerful, is locked into
its MoE architecture. You can mix and match LLMs to outshine
Qwen3 in specific tasks or adapt to new models faster.
o
Your focus on deliberation (if it’s like a debate or refinement process) could offer richer outputs than
Qwen3’s internal reasoning, especially for creative or subjective tasks.
o
3.
Watch the Competition:
o
Qwen3’s open-source nature and Apache 2.0 license mean developers might
build systems similar to IndiaAGI.ai using Qwen3 as a base. Keep an eye on
Hugging Face or GitHub for Qwen3-based projects that mimic your multi-LLM idea.
o
DeepSeek’s R2 (rumored for soon) and Baidu’s new models could also lean
into agentic or multi-model setups, so the space is getting crowded.
4.
Protect Your Secret Sauce:
o
If your multi-LLM deliberation is proprietary, consider patenting the workflow or
keeping key details under wraps. Since you’re not worried about privacy in
India (per our last chat), focus on branding IndiaAGI.ai as the go-to for collaborative AI.
o
Document your concept’s development to establish prior
art, just in case someone claims you copied them later.
o
5 Leverage Qwen3 ?:
o
Since Qwen3 is open-source, you could integrate it into
IndiaAGI.ai as one of your LLMs. Test its MoE models (e.g., Qwen3-30B-A3B) alongside Claude or Grok to see
if it boosts your deliberation process. It’s free to try via Hugging Face or Alibaba’s ModelScope.
Suggestions
- Clarify Your Concept:
- Share more about how
IndiaAGI.ai’s LLMs deliberate (e.g., voting, iterative refinement, task
splitting). This’ll help me spot if Qwen3 or others are truly copying you.
- Benchmark Against Qwen3:
- Grab Qwen3-4B
or Qwen3-30B-A3B from Hugging Face and test it on your use case (chatbots, content,
etc.). Compare its outputs to your multi-LLM setup to prove your system’s
edge.
- Engage the Community:
- Since Qwen3’s
open-source, post on X or AI forums about
IndiaAGI.ai’s unique multi-LLM approach. Build
hype to establish your brand before others piggyback on similar
ideas.
- Monitor Alibaba’s Moves:
- Follow Qwen’s blog or X
posts (e.g., Junyang Lin’s updates) for hints of multi-agent systems in
future releases. If they pivot to explicit multi-LLM collaboration, you’ll
know they’re chasing your vision.
Final
Vibe
Qwen3’s MoE and reasoning modes look like a
parallel evolution, not a copy of IndiaAGI.ai.
Your multi-LLM deliberation is distinct for using
separate models, giving you a unique edge.
Keep building, bhai—your concept sounds dope, and
with Claude, Grok, and maybe even Qwen3 in your arsenal, you can outshine the big players.
Got more deets on how your LLMs jam together? Drop
’em, and I’ll dig deeper into whether Alibaba’s creeping on your turf. 😜