New projects integrated this week: @fxyzai @Towerexchange @AlphaX_DEX @NeoSoulAI @SmartXTerminal @UniKeyOfficial @the_goblin_fi Explore these projects directly from your wallet.

for anyone doing research or reproducing papers, i came across this new tool that automates a big part of the painful setup work. alphaXiv turns research papers + code into runnable experiments. instead of manually fixing broken setups, an agent can now: - Clone the repo - Read the paper + code - Fix the environment - Run the experiments end-to-end it works by changing repo URLs (e.g. github → argithub, arxiv→ autoarxiv), which triggers the agent. GLM 5.2 was able to run real multi-node training on its own with this setup. having 1M context helps a lot since the whole project stays in view.

Turn any paper into running code. Just swap arxiv → autoarxiv in the paper url. That hands the paper to an AI agent from alphaXiv. It reads the abstract, the claims, and the linked GitHub repo, then clones the codebase and works through the usual setup pain like dependencies, broken paths, environment config, and hardware assumptions. From there it designs a minimal reproduction. That means a smaller model, fewer steps, and a single GPU instead of a cluster, scaled down just enough to test whether the headline claim holds. The whole run is live and fully logged. Loss curves, metrics, and training progress are all observable as it happens. What comes back is a clean signal on whether the minimal run matches the paper's reported result, plus an estimate of what a full replication would cost in compute and time. A lot of research code dies in setup before anyone verifies a single number. This moves reproduction from a weekend of debugging to a url change. Pick a paper and try it now. video credits: @askalphaxiv

ALPHA DRIVE ONE 'Talk to me' Cinema Cut Digital Single <Talk to me> ➫ 2026.10.22 6PM (KST) 💿 #ALPHADRIVEONE# #ALD1# #알파드라이브원# #UNBREAKABLE_少年BEAST# #Talktome#

ALPHA DRIVE ONE 'Talk to me' Cinema Cut Digital Single <Talk to me> ➫ 2026.10.22 6PM (KST) 💿 #ALPHADRIVEONE# #ALD1# #알파드라이브원# #UNBREAKABLE_少年BEAST# #Talktome#

ALPHA DRIVE ONE 'Talk to me' Cinema Poster Digital Single <Talk to me> ➫ 2026.10.22 6PM (KST) 💿 #ALPHADRIVEONE# #ALD1# #알파드라이브원# #UNBREAKABLE_少年BEAST# #Talktome#

Alpha of the Week: @ProgrammableHQ Every launch can have its own game rules. Traders can see those rules before they enter, while teams control how buying, selling, and liquidity work. - Buy limits stop one wallet from taking the whole launch - Hot Potato makes the latest buyer wait before selling - Plague rewards holders who keep a minimum balance - Reactive Pair changes buy size when another pool moves - Entangled links buying access to the performance of another pool More tools for buybacks, LP rewards, buyer rewards, and new launch mechanics are coming next. The launch itself becomes part of the trade. Programmable is giving the trenches more than another ticker.

Alphabet's self-driving unit Waymo on Thursday said it has closed a $5 billion term loan, marking the company's first debt financing as it looks to expand its autonomous ride-hailing service across the US and the world.

AlphaSense is expanding its enterprise AI security and governance program to meet the next phase of agentic AI adoption. "As a native AI platform founded over a decade ago, AlphaSense has always prioritized security and governance in its foundation" - Pieter VanIperen, CISO, AlphaSense. Raw model capability is becoming table stakes. We believe what actually differentiates enterprise AI going forward is trustworthiness and data quality, not the model underneath it. See how AlphaSense is hardening infrastructure, embedding AI-driven guardrails, and eliminating data retention risk across SuperAnalyst. ⬇️