Trend Engine: AI-Powered News & Trends

Easy to put together, not super expensive. Options for the Moon phase, sunrise/sunset time and UV Index, so you would be able to see if the Moon influences the timechain and when to sun your balls 😀
Short video demo: [https://www.youtube.com/watch?v=7DtQNCBLffI](https://www.youtube.com/watch?v=7DtQNCBLffI)
Github: [https://github.com/kovrom/circle](https://github.com/kovrom/circle)

AI-generated content is easy to spot these days:

– The em dashes
– The “It’s not X, but Y”
– Snappy one-line sentences
– Lots of emojis
…

Many of us use AI to edit text, build chatbots, write reports…
What technique do you use to make sure the output isn’t generic AI slop?

Do you use specific prompts? Few-shot examples? Guardrails? Certain models? Fine-tuning?

Facing hiccups with the PumpFarm bot can be frustrating, but with the right troubleshooting steps and potentially exploring new tools, you can continue managing your Telegram groups efficiently. Always stay updated with the latest in community forums or official channels to keep your operations running smoothly. Remember, technology is ever-evolving, and there are myriad solutions out there—sometimes, a quick conversation or a post in a forum like Reddit can lead to the answer you need. Happy exploring!

Over the past few months, we’ve been working with a group of builders in the Aptos ecosystem to design a 4-week virtual accelerator tailored for early-stage Web3 founders.

It’s fully remote, focused on helping founders get their MVP and pitch ready. There’s hands-on mentoring, tech guidance, and it ends with a Demo Day where teams can pitch for up to **$50K in funding**.

We’re doing a small beta cohort (just 10 teams). Applications close July 18.

Not trying to promote — just curious if others have been part of similar early-stage programs and what made them worthwhile?

If anyone’s curious about this one, I’m happy to share more in the comments.

Hi there!

I’d like to share a project I’ve been working on over the last few months; **Echoes of GaIA** is a hybrid framework for modeling evolution and running biome simulations with “*living*” ecosystems using lots of AI techniques. For context, I’ve been working quite a few years in the software and videogame development world, but four years ago I went back to university (hasn’t been easy at this stage of life, but I just finished a few days ago and finally pulled out a huge thorn I’d had for more than 15 years) and this has been my capstone project. I specialized in Computation theory and Artificial Intelligence and wanted to create a kind of ode to AI and tackle biomes holistically, since I was eager to learn all these techniques and the underlying math.

The idea was to shape a project that – although just a very modest, small gesture, symbolic I’d say – tries to contribute something toward helping heal the planet, improving climate change, etc., through Artificial Intelligence. I just wanted to share it because I think it might interest people reading this subreddit, and I cover some pretty current topics that I believe are very important.

Anyway, some of the things I’ve implemented:

• Climate and fauna agents based on **Reinforcement Learning**

• **Genetic algorithms** for species **evolution**

• “Equilibrium” agent (**neurosymbolic AI**) – the idea here is to balance the whole ecosystem (for now using **LSTM multivariate multihorizon with attention** and expert systems and/or **graphs** as the knowledge base)

• I also do c**omputational modeling** (but on its discrete side, not continuous) of many biological and physiological processes

It can be extended easily (I used ECS so I could have a modular component system for the biological processes of flora and fauna entities) and I’ve also put together a snapshot viewer and real‑time metrics (InfluxDB + Grafana).

Project website → [https://www.echoes-of-gaia.com](https://www.echoes-of-gaia.com) (turn on **sound** before clicking!! I’m quite a big nerd and wanted to set a proper ambiance)

GitHub repo → [https://github.com/geru-scotland/echoes-of-gaia](https://github.com/geru-scotland/echoes-of-gaia)

If anyone’s interested in the technical report, it’s available on the site as **Main Doc** and there’s also a document covering the project’s basic foundations, architecture, and main systems **Architecture doc** (those documents are only available in Spanish, unfortunately).

Any suggestions are more than welcome and, if you like it, I’d appreciate a star on GitHub. Thanks!

Hey r/quant!

We’re Monkey Tilt – a crypto-first online casino operating at the intersection of gaming, trading, and entertainment. We’re building a platform that blends real-money gaming with modern creator-led culture, and we’re looking to expand our quantitative capabilities as we scale.

We’re hiring a **Quantitative Risk Analyst** as an **Intern or Full-Time Role** to take ownership of risk modeling and exposure management across our gaming products. You’ll be working directly underneath our current Head of Risk.

# Role Overview:

This role sits at the core of our platform economics. You’ll be responsible for developing models to monitor, forecast, and manage risk across thousands of games and users. The work is a mix of statistical modeling, real-time exposure analysis, and simulation-based forecasting. We’re looking for someone who can bring a quantitative lens to questions like:

* What is our true max exposure per game or per user?
* How do we dynamically adjust limits and volatility thresholds?
* Can we model win/loss distributions more accurately for better forecasting?
* How do we balance product growth with long-term sustainability?

# Ideal Background:

* Strong quantitative foundation – statistics, mathematics, or engineering
* Experience with simulations, risk modeling, or forecasting frameworks
* Comfort with Python (pandas, NumPy, SciPy, etc.)
* Familiarity with gaming, trading, or crypto ecosystems is a plus
* Able to work independently and make decisions with limited structure

# Bonus:

* Experience in iGaming or sports betting (on either side of the table)
* Knowledge of game RTP, volatility curves, payout distributions
* Experience building real-time dashboards or alerting systems

# What We Offer:

* Competitive compensation. Likely to start around \~$100k, highly negotiable depending on experience (as well as if you’re interning).
* Flexible work location; can be fully remote
* A small, fast-moving team with direct access to product and executive leadership
* High-impact work – your models directly influence platform health and profitability

We’re not building a traditional casino. We’re building an entertainment and trading platform where risk is core to the product. If you’re a quant who enjoys working with real-world data, making systems more resilient, and operating in fast-moving environments – we’d love to talk. Feel free to DM me for contact information or to inquire about the role.

Been messing around with different Web3 apps lately, and man… some of them are still *way* too complicated.
Wallet popups, gas fees, multiple confusing steps just to do something basic — it’s a lot.

It’s kind of crazy how much tech we’ve built under the hood, but the actual user experience still feels stuck.
Like, imagine trying to explain MetaMask + bridging + staking to someone new — they’d be out in 5 minutes.

I really think if Web3 is going to grow, it needs less “innovation” and more “make it easy to use.”

Just sharing a thought — curious if anyone else feels this too.

# “What if AI gets so smart that the President of the United States cannot do better than following ChatGPT-7’s recommendation, but can’t really understand it either? What if I can’t make a better decision about how to run OpenAI and just say, ‘You know what, ChatGPT-7, you’re in charge. Good luck.”