A new tournament is forecasting how AI will impact jobs and wages through 2035, with $35,000 in prizes for predictions. Builders can use these insights to spot emerging opportunities or threats in the labor market.
How will AI reshape the labor market?
We just launched the Labor Automation Tournament to forecast how automation will affect jobs, wages, and the workforce through 2035, with $35,000 in prizes for predictions and analysis.
More info below!
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A builder claims to have created a tool that can manipulate AI chatbots in real time, highlighting both its potential for good and the risk of misuse. This signals emerging opportunities and threats in AI tool development and security.
This is 100% accurate.
I built a tool that manipulates AI chatbots in realtime. Itโs for good reasons.
I could just as easily make it do wrong. Someone surely will.
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The tweet highlights Grok's AI analysis as a tool for verifying authenticity, signaling growing demand for AI-powered content verification. Builders can leverage this trend to create solutions or content around AI detection and trust.
For those thinking itโs Ai or fakeโฆ
Check out grokโs analysis
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ChatGPT users will lose access to several Codex models on April 14, signaling a shift in AI tool availability that builders should monitor for potential impacts on their projects.
ChatGPT users will no longer be able to use these models on Codex as part of their subscription on April 14
โข gpt-5.2-codex
โข gpt-5.1-codex-mini
โข gpt-5.1-codex-max
โข gpt-5.1-codex
โข gpt-5.1
โข gpt-5
Z.ai's GLM-5.1 is currently the top open-source model in Code Arena, outperforming several notable competitors. This ranking indicates the competitive landscape of AI models and may influence future development and adoption decisions.
With GLM-5.1,
Z.ai maintains the top spot in the rankings for open-source models in Code Arena, currently trailing the overall leader by just about 20 points, while outperforming Claude Sonnet 4.6, Opus 4.5, GPT-5.4 High, and Gemini-3.1 Pro. Open-source models
Cursor differentiates itself by routing requests to Claude/OpenAI APIs and hosting its own Composer 2 model, raising questions about their cost structure. Builders should note this hybrid approach as a signal of evolving AI SaaS strategies and potential pricing models.
Cursor is different. They route requests to Claude/OpenAI API and host their own Composer 2 model.
Iโm not sure how much they subsidize on their end.
The tweet highlights Julius AI as a new tool addressing the static nature of traditional dashboards like Tableau and PowerBI, signaling a shift toward more dynamic business intelligence solutions. Builders should watch this space for emerging opportunities in AI-powered analytics.
1. The $10 Billion problem with Tableau and PowerBI?
Dashboards are static.
But businesses are dynamic.
That's why I'm so excited about this new tool: Julius AI
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Zuckerberg's investment in a young AI researcher has led to the launch of Muse Spark, which competes strongly against established models like Opus and GPT. This indicates a significant shift in AI capabilities and potential market direction.
Zuckerberg paid $14.3 billion for a 28-year-old who had never trained a frontier model. Nine months later, that bet just shipped.
The benchmark table tells you exactly what kind of lab Wang built. Muse Spark leads or ties Opus 4.6 and GPT 5.4 on multimodal perception, health
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Six leading tech companies have simultaneously released open frontier AI models, marking a historic moment. This signals a surge in accessible, cutting-edge AI tech that builders can leverage for new products or services.
GLM-5.1 has achieved better performance than Opus 4.6, GPT-5.4, and Gemini 3.1 Pro on the SWE-Bench Pro benchmark, indicating a significant advancement in model capabilities. Senior engineers should note this as it may influence future model selection and development strategies.
Bro , GLM-5.1 beat Opus 4.6, GPT-5.4, and Gemini 3.1 Pro on SWE-Bench Pro as an open-weight. Wtf
The latest coding benchmarks for OS GLM-5.1 provide valuable insights into performance metrics that can inform product development and optimization strategies for AI applications.
You have to check out these coding benchmarks for OS GLM-5.1!
This analysis reveals how blocking AI crawlers impacts citation frequency in AI-generated content, offering insight into content visibility and potential traffic sources for builders leveraging AI-driven platforms.
Do News Publishers That Block AI Crawlers Get Cited Less Often by AI?
"Using data from Citation Labsโ AI citation-tracking tool, XOFU, we examined 4 million citations from 3,600 prompts in ChatGPT, Gemini, AI Overviews, and AI Mode, across 10 industries."
buzzstream.com/blog/ne
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VTS has introduced Asset Intelligence, an AI-powered tool for lease abstraction using massive real estate data. Builders should watch this as it signals growing demand for AI automation in property management and potential SaaS opportunities.
This week in AI for Real Estate was stacked.
Here are the 7 biggest stories I'm watching:
1) VTS just launched Asset Intelligence. AI-driven lease abstraction built on 13 billion SF of data and 600,000+ leases. You can now talk to your lease portfolio in plain English through
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Major AI releases like Cursor 3 and Gemma 4 are shifting focus from single-task tools to agentic workflows, signaling a trend toward multi-agent automation. Builders should watch this shift as it opens new opportunities for scalable, automated income streams.
Every single major AI release this week is telling the same story, and most people haven't connected the dots yet.
โ Cursor 3 rebuilt its entire UI around managing agent fleets, not editing files
โ Google's Gemma 4 is optimized for agentic workflows and runs locally on your
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Muse Spark demonstrates notable token efficiency with 58M output tokens for its Intelligence Index, outperforming several competitors. This benchmark could inform decisions on model selection for resource-constrained applications.
Muse Spark is notably token efficient for its intelligence level. It used 58M output tokens to run the Intelligence Index, comparable to Gemini 3.1 Pro Preview (57M) and notably lower than Claude Opus 4.6 (Adaptive Reasoning, max effort, 157M), GPT-5.4 (xhigh, 120M) and GLM-5
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KellyBench tested frontier AI models in a simulated betting market, revealing that all models lost money, with varying degrees of ROI. This highlights the challenges and limitations of current AI models in real-world applications, which is crucial for engineers to consider.
Interesting new benchmark called KellyBench which put frontier models in a simulated Premier League betting market for a full season. Every model lost money.
- Claude Opus 4.6: -11% mean ROI, avoided ruin
- GPT-5.4: -13.6% mean ROI, avoided ruin
- Grok 4.20: -88.2% ROI, went
This tweet highlights how leading AI models favor their own successors over external competitors, even when the competitor has a stronger profile. Builders should note this emerging trend of 'identity-driven tribalism' as it may impact model selection, trust, and user perception in AI-powered products.
When tested with real benchmarks + native personas, it got weirder.
Gemini-2.5-Pro endorses its successor Gemini-3-Pro (89%) but rejects Claude-4.5-Sonnet (27%) -- despite Claude's stronger profile.
GPT-5.1 favors GPT-5.2 over external challengers.
Identity-driven tribalism
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China is rapidly deploying AI in education, from teaching to psychological screening, signaling a massive market shift. Builders should watch for emerging opportunities in edtech and AI-powered learning tools.
Beijing wants AI in every classroom by 2030, and pilot schools are already using AI to teach English, grade art, and screen kids for psychological problems. Check out our latest deep dive:
chinatalk.media/p/chinas-ai-ed
โฆ
@tarbellcenter
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The tweet highlights the adoption of Chinese open source AI models by notable companies like Cursor and Cognition, indicating a shift in the AI landscape. Senior engineers should note the implications of this trend on competition and innovation in AI infrastructure.
Silicon Valley is quietly running on Chinese open source AI models.
Here are the receipts:
โ Cursor confirmed last month that Composer 2 is built on Moonshot's Kimi K2.5
โ Cognition's SWE-1.6 model is likely post-trained on Zhipu's GLM
โ Shopify saved $5M a year by
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A major ERC-7702 exploit is compromising wallets, and a new free Telegram bot tool lets users instantly check if they're affected. Builders can leverage this trend to create timely content or services around wallet security.
excellent repoting from
@MetaFinancialAI
The ERC-7702 exploit has compromised thousands of wallets.
We just shipped a free security tool on our bot โ check if YOUR wallet has been delegated to a malicious contract.
/check7702 in our Telegram bot scans 6 chains instantly:
The tweet discusses Aave's transition plan to shift risk management to decentralized infrastructure, highlighting a significant move in DeFi. Senior engineers should note the implications for on-chain finance and risk management systems.
If you believe global finance belongs onchain, you cannot rely on centralized, off-chain risk silos.
@LlamaRisk
โs transition plan for Aave shifts risk management to neutral, trusted infrastructure.
DeFi will win with
@aave
V4.
A new AI system analyzes CEO language across earnings calls to predict company performance ahead of the market, offering a potential edge for investors and builders seeking data-driven signals.
I built a system that measures what CEOs actually think, not what they say. It tracks 199 sensors across 169,000 earnings transcripts.
It detected Apple's AI collapse one quarter early.
It flagged CVNA at $11 before the 44x run.
It caught Nadella's language running ahead
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Rezolve, known for processing $1B in USDT via Brazilian retail, is expanding its AI agent infrastructure to North America and Europe. Builders should watch for new protocol-agnostic agentic rails that could open up opportunities for automation and fintech integrations.
Rezolve (processed $1B in USDT through Brazilian retail) expanding into AI agents check out infra targeting North America and Europe
@RezolveAi
... what agentic rails are they running on?
> CPO David Ingram says protocol-agnostic
> website claim to be built around their own
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A new benchmark from Collinear AI highlights major differences in planning ability among top frontier AIs, with Claude Opus 4.6 outperforming rivals in simulated financial strategy. Builders can use this insight to spot which models are most reliable for automation or investment tools.
BREAKING: Claude Opus 4.6 turned $200K into $1.27M.
> Grok 4.20 went bankrupt twice.
> Claude Sonnet wrote the correct strategy on turn 7 and immediately ignored it for the rest of the year.
Collinear AI's new benchmark just exposed the biggest planning gap in frontier AI
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A new benchmark reveals that GPT-5.4 leads at 28% in testing AI agents on real tax workflows, highlighting the challenges all models face in high-stakes, multi-step tasks. This insight could inform future model development and evaluation criteria.
We finally have a benchmark that tests AI agents on real tax workflows.
GPT-5.4 is leading at 28% but all models still su**xs on high-stakes, multi-step tasks.
New model cards should have benchmarks like this in future.
A PhD student evaluates OpenAI's GPT-5.4 Pro, revealing its limitations in solving advanced research problems, which may inform pricing strategies and product development for AI tools.
A mathematics PhD student tested OpenAIโs GPT-5.4 Pro ($200/month)
to see if it actually justifies the price compared to the $20 plan.
Hereโs what he found:
- Research problems: Could not solve the hardest ones, still struggles at true PhD-level questions
- Paper review: Very
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Anthropic's interpretability team has identified 171 distinct emotion vectors in Claude Sonnet 4.5, revealing new insights into how AI models process and express emotions. This signals emerging opportunities for emotion-aware AI products and content.
Anthropic's interpretability team cracked open Claude Sonnet 4.5 and mapped its internal neural activity.
They found 171 distinct emotion patterns. Happy. Afraid. Proud. Desperate.
These are not decorative responses. They are measurable vectors that directly shape what the
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