AFTERPARTY™️ retweeted
Transform your social media & company data with enterprise-grade sentiment analysis 📊
ReadyAI delivers ScaleAI-level accuracy at a fraction of the cost. No human annotation needed.
Try it FREE now: readyai.ai/p/data_pipeline
Built on $TAO 🔥
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AFTERPARTY™️ retweeted
Our team brings together founders with billion-dollar exits, deep AI/ML expertise, and decades of experience with giants like Google, Disney and Intuit. Building the future of AI data infrastructure @ReadyAI_ 🤝
Our strategic vision and roadmap in detail 👇
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Excited to be building crypto x AI in the USA 🇺🇸
Great conversation in DC with @SenLummis, @MarshaBlackburn, @SenatorTimScott & others on keeping innovative crypto companies in the US. They recognize how crucial crypto & AI are to our nation’s competitiveness. Excited to keep working together to drive this innovation forward 🇺🇸
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AFTERPARTY™️ retweeted
With dTAO launching tomorrow, we want to share our full strategic vision and roadmap for @ReadyAI_ on $TAO
Try our structured data product today for free here: readyai.ai/p/data_pipeline
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👀👀
ReadyAI 2.0 is here!
Process raw data from ANY Huggingface dataset into structured outputs
Get your data AI-ready
It’s a big leap toward decentralized Scale AI.
Try it now: readyai.ai/p/data_pipeline
Also see our roadmap for the next 6 months 👇
ReadyAI 2.0 is here! AI-Ready Data with the Jobs Interface
ReadyAI just launched our Jobs Interface Beta, a powerful frontend that enables organic queries on Subnet 33. This new interface allows end users to process raw data from any Huggingface dataset into structured outputs tailored to their needs. Try it now: readyai.ai/p/data_pipeline
This milestone is a significant step toward our vision of becoming a decentralized Scale AI. ReadyAI empowers individual developers and enterprises of all sizes to make their data AI-ready, seamlessly integrating it into AI models and applications.
Organic Queries: The Next Era for the ReadyAI Ecosystem
We have initiated the next phase of our journey with the introduction of organic queries into the miner incentive system. This phased rollout ensures:
Fair Miner Scoring: Maintaining fairness and high-quality outputs for all contributors.
Structured Data Integration: All Tagging queries processed through the Jobs Interface will now be scored alongside conversation data.
New Data Sources: Social media data, starting with SN13 Dataverse Reddit data, will be incorporated as an organic query source.
Data tagging and structuring are pivotal steps in the AI Agent pipeline. With the increasing demand for real-time, high-quality data for retrieval-augmented generation (RAG) systems and fine-tuned models, ReadyAI is uniquely positioned to lead this transformation. Over the next couple of months, we will showcase AI Agents powered by our structured data pipeline.
6 Month Roadmap
1. Organic Queries / Jobs Interface
Initial Rollout: Organic Tagging queries are live via the Jobs Interface on readyai.ai/p/data_pipeline right now and are being processed by the ReadyAI validator.
Other validators may adopt this new branch, but we will be testing with ours to ensure vTrust and tag quality remains high before rolling this out more broadly.
Social Media Data Expansion: After validating the initial rollout, we plan to increase the proportion of validator windows processed from social media datasets from Macrocosmos Dataverse (SN13).
2. Incentive Design 2.0
Enhanced Capabilities: We are upgrading our incentive system to support metadata tagging for arbitrary text data. This includes single-label and multi-label categorization.
Competitive Positioning: These improvements will achieve product parity with Scale AI's structured data offerings, reinforcing ReadyAI's position as a high-quality, cost-effective alternative.
3. AI Agent Launches Powered by ReadyAI
AI Agent Partners: We are collaborating with partners to launch AI Agents powered by ReadyAI's structured data pipeline within the next 1–2 months.
These AI Agents will demonstrate the power of structured data pipelines for RAG systems and real-world applications.
4. Integrating Data Scraping with SN13
ReadyAI as the Data Frontdoor for Bittensor: We are collaborating with SN13 to incorporate data scrapping and structuring on data into our frontend.
We are currently validating on SN13 and starting to provide structured data around Reddit/Twitter datasets they have created.
Next up: enable users to choose data for scrapping and then data structuring.
5. Enterprise Sales
New Leadership: We recently hired a Director of Sales with a proven track record of driving $15 million in software sales over the last two years.
Accelerated Growth: With the Jobs Interface live and increasing demand for structured data, we are scaling our enterprise sales offerings to onboard new customers.
6. Image/Video Metadata Tagging
Integration Testing: Image metadata tagging, a critical business line for Scale AI, is being tested for integration into the subnet.
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AFTERPARTY™️ retweeted
ReadyAI 2.0 launching next week...can't wait to show you what we have been cooking up for dTAO
$TAO
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AFTERPARTY™️ retweeted
100%
Consumer AI agent are the frontend
Bittensor subnets are the backend
The success of Virtuals/ai16z in consumer AI agents and Bittensor subnets' work on decentralized AI infrastructure are complementary.
As agents scale in TVL and influence, robust training/inference infrastructure becomes even more vital.
More consumer facing apps and subnets coming soon from the Bittensor eco—stay tuned!
Shoutout @virtuals_io—my former team @DeFianceCapital backed them pre-rebrand and their pivot to the agent economy has been nothing short of incredible.
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AFTERPARTY™️ retweeted
We are looking for a ROCKSTAR developer to join our team @ReadyAI_ and there is something in it for YOU
If you refer the candidate we hire, we will gift your choice of either $10K in Cash or $BTC or $11,111 in $TAO
You get upside as we push $TAO
Job description / FAQ👇
linkedin.com/jobs/view/40826…
FAQ:
-Yes, this is real.
-Yes, this job is legitimately badass. Working with ex-Google, Intuit, Disney team. If you refer someone, they will be psyched.
-Yes, you can refer yourself and get this as a signing bonus.
-Just one signing bonus per hire. Can be split for two-step referral. You need to be the first one to have introduced and if the person themselves submits first they receive the signing bonus and there is no referral.
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AFTERPARTY™️ retweeted
Really enjoyed chatting with Grant @VenturaLabs about the importance of structured data for AI models and the future of @ReadyAI_ on Bittensor 🫡
SN3⃣3⃣
$TAO
@opentensor
Ventura Labs Ep. 7 - David Fields
David (@DavFields) is the Founder of ReadyAI (@ReadyAI_) and Afterparty (@afterparty)
Timestamps:
0:55 - Introduction
1:36 - What is ReadyAI
4:40 - The Team Behind ReadyAI
7:58 - The Significance of Bittensor
11:15 - Impact of EVM Smart Contracts
14:50 - Importance of Structured Data
16:37 - ReadyAI Approach to AI
19:19 - Decentralization vs Centralization
23:18 - Performance Metrics
25:25 - Future Direction
28:09 - Social Media Data
32:13 - Expanding to Vision
35:34 - Roadmap
37:11 - dTAO
44:07 - Commercialization of Subnets
49:10 - How to Find Product Market Fit
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AFTERPARTY™️ retweeted
ReadyAI is 600x cheaper and 71% more accurate than human annotation services
This unlocks the power of structured data and AI for everyone not just big tech
$TAO
Clip From: Hash Rate - Ep. 74: @ReadyAI_ Bittensor SubNet 33 - 'Decentralized Scale.AI'
🧙♂️Guest: @DavFields
Full Ep:
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AFTERPARTY™️ retweeted
Enjoyed chatting with @markjeffrey about our plans with @ReadyAI_ to build a decentralized ScaleAI on $TAO
Data annotations done with @ReadyAI_ are already 71% more accurate than MTurk benchmark and 600x cheaper.
And we are just getting started 🫡
@opentensor
Hash Rate - Ep. 74: @ReadyAI_ Bittensor SubNet 33
🧙♂️Guest: @DavFields
'A Decentralized ScaleAI' on $TAO
00:00 Introduction to BitTensor and ReadyAI
02:53 David Fields' Background and Experience
06:12 Understanding Scale AI and Its Market Position
09:02 The Role of LLMs in Data Annotation
12:10 Cost Efficiency and Accuracy of ReadyAI
15:00 Disruption in the AI Data Annotation Market
17:53 The Importance of Human Feedback in AI
20:46 Why Choose BitTensor for AI Solutions?
24:05 Dynamic Tao and Its Implications
27:02 Exploring Other Subnets and Community Engagement
29:54 The Future of BitTensor and Its Ecosystem
33:13 Dynamic Tao Explained
36:04 Competition in the Decentralized AI Space
Ledger: shop.ledger.com/HashRate
Messari Pro (15% off code): MARKJEFFREY15
Also Available on YouTube / Apple / Amazon / Spotify
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AFTERPARTY™️ retweeted
ReadyAI is delivering 71% MORE ACCURATE structured data for AI models at 600x LOWER COST than human annotation services like MTurk and ScaleAI
All this in our first 100 days since launch and we are just getting started 🫡
Presentation on our roadmap at the Bittensor meetup👇
$TAO @opentensor 🤝 @ReadyAI_
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Afterparty and @ReadyAI_ continuing to innovate and democratize access to the best AI tools for all creators and businesses
ReadyAI is delivering 71% MORE ACCURATE structured data for AI models at 600x LOWER COST than human annotation services like MTurk and ScaleAI
All this in our first 100 days since launch and we are just getting started 🫡
Presentation on our roadmap at the Bittensor meetup👇
$TAO @opentensor 🤝 @ReadyAI_
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What a day! Thank you for hosting an incredible event @jasminervaa
Had a great time hosting the 2nd community event with @opentensor and 6 #Subnets @TensorplexLabs @getmasafi @afterparty @omron_ai and @404gen_ @openkaito in SG 🇸🇬
Hope everyone enjoy the vibe of the best community $TAO ❤️
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AFTERPARTY™️ retweeted
ReadyAI is building a decentralized Scale AI
Instead of human annotators, we are using distributed LLMs
In just 3 months, our top miners are now exceeding the MTurk benchmark by 71% and GPT 4o by 37%
Previous studies saw only a 25% increase over the MTurk bench for ChatGPT.
Read more 👇
readyai.ai/p/readyai_benchma…
Summary of Findings:
This study evaluates the performance of miners using their own fine-tuned models in comparison to the Mechanical Turk (MTurk) benchmark, which is used as the gold standard for comparing LLMs for annotation tasks. Previous studies, such as Gilardi, Fabrizio et al. (2023), "ChatGPT Outperforms Crowd Workers for Text-Annotation Tasks," showed that ChatGPT outperformed the Mechanical Turk benchmark by 25% on average.
Miners on subnet 33 are currently outperforming the MTurk benchmark by 71% and GPT 4o with no further optimizations by 37%. SN33's top miner performance has improved 75% over the three months since the subnet's launch.
Two other key considerations in LLMs vs. MTurk performance are cost and time to complete tasks. For time to complete a task, the average for MTurk was 3 minutes and 57 seconds per task. For costs, MTurk averages $0.12 per task. SN33 miners are producing these annotations at a cost of 660x less. Additionally, recent research from the Swiss Federal Institute of Technology suggests that a substantial portion of crowd workers may be leveraging Large Language Models (LLMs) to complete their tasks. Specifically, Veselovsky et al. (2023) estimate that between 33% and 46% of crowd workers utilized LLMs during task completion. Enterprises are paying human costs for LLM work that is 660x cheaper to produce using SN33.
Structured data is the foundation of successful AI models and applications, and it requires high-quality, trusted data labeling pipelines. Annotations are critical in transforming raw information into high-quality, organized datasets that fuel AI development and performance. The data annotation process for AI development faces significant challenges of cost inefficiency, temporal constraints, limited scalability, and annotation inconsistency.
The findings of this study provide compelling evidence for the efficacy of ReadyAI's innovative, cost-efficient structured data pipeline. Our novel approach demonstrates significant innovation in addressing the challenges in traditional data annotation processes.
$TAO @opentensor
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AFTERPARTY™️ retweeted
Excited to speak alongside some of my favorite DePIN founders during Token 2049 at DePIN Founders Day
Join us! 🫡
lu.ma/qx7l81vd
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AFTERPARTY™️ retweeted
Excited to co-host this with some of our favorite builders and investors in $TAO @opentensor
Come join us for a great discussion on all things Bittensor 🫡
@afterparty @ReadyAI_ @jasminervaa @TensorplexLabs @_kaitoai @myshell_ai @inference_labs @404gen_
Join us for the 2nd @opentensor Asia Community Meetup during #Token2049 🇸🇬!
There has seen many exciting developments and it is a perfect opportunity for the ecosystem to come together!
$TAO
lu.ma/wlm6qt2a
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AFTERPARTY™️ retweeted
Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1
In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive.
Today we announce SN33 is now @ReadyAI_ to fully align with our mission 👇
SN33 is building a more performant and significantly cheaper alternative to Scale AI
Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI
It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly.
SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: readyai.ai/p/readyai_llmoil
Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth.
We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline.
We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀.
Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO @opentensor
1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”
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AFTERPARTY™️ retweeted
The Structured Data Pipeline @ConversationGen creates Super AIs
AI Models with:
- 99.9% Factual Accuracy
- Consistency in tone and personality of the company & its founders
We are bringing the power of Super AIs to all Bittensor subnets soon 👀
Try the Super AI for SN33 now 👇 conversations.xyz/p/sn33_sup…
$TAO @opentensor
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AFTERPARTY™️ retweeted
Excited to join our friends in Singapore at #TOKEN2049 and chat all things Bittensor with some of the best builders and investors in the space
@jasminevaa
@_kaitoai
@TensorplexLabs
@0xai_dev
🫡
See you there! $TAO @opentensor
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