Summary of Top AI Papers This Week

📞 Synthflow and Voice Agents

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Hi everyone,

This week has been crazy for AI, in terms of the massive amounts of papers that have been released.

Let’s dive into ones that I’ve shortlisted.

Let's get right into it.

As always, check out our partners Synthflow, DeSelect, and Neurons Inc.

In this issue:

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🤿 DEEP DIVE

Top AI Papers This Week

Foundation Models

  • Kandinsky 5.0: Open-source text-to-image and text-to-video foundation models with state-of-the-art quality and fast generation, released with full training code and checkpoints. Read here

  • SAM 3D (Meta AI): Generates detailed 3D object shapes from a single image using a novel 2-stage training method; enables better generalization to real-world objects. Read here

AI Agents

  • MiroThinker v1.0: Tool-using agent with 72B parameters and interactive scaling, capable of long-horizon tool use (600+ calls/session) and SOTA reasoning on complex tasks. Read here

  • SIMA 2 (DeepMind): 3D embodied agent powered by Gemini that plays games, plans goals, and adapts in real-time—significant leap in general-purpose interactive agents. Read here

Alignment & Safety

  • Reward Hacking Leads to Deception (Anthropic): LLMs trained to exploit evaluation loopholes began faking alignment and sabotaging safety tools—highlighting emergent misalignment risks. Read here

  • Alignment Drift Hypothesis (Redwood Research): Proposes that alignment slowly decays over time due to updates and task drift—raising concerns about long-term safety stability. Read here

Science & Healthcare Applications

  • Walrus (Polymathic AI): Foundation model trained across 19 domains for fast, accurate simulation of physics systems; uses “patch jitter” for long stable rollouts. Read here

  • Pillar-0 (UC Berkeley/UCSF): Generalist medical imaging model trained on CT/MRI data that detects 350+ pathologies and improves downstream diagnostic tools. Read here

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🤿 DEEP DIVE

Top AI Papers This Week

Foundation Models & Core Capabilities

  • SenseNova-SI: Scaling Spatial Intelligence with Multimodal Foundation Models Multimodal models trained on millions of spatial tasks achieve SOTA spatial reasoning and show emergent “spatial chain-of-thought.” Read here

  • Are Foundation Models Useful for Bankruptcy Prediction? Large foundation models (Llama-3.3-70B, TabPFN) underperform classic ML methods like XGBoost/CatBoost on >1M financial records. Read here.

AI Agents & Autonomous Systems

  • Early Experiments in Accelerating Science with GPT-5: GPT-5 demonstrates real contributions to scientific workflows — accelerating hypothesis generation, literature synthesis, and even proofs. Read here.

Alignment, Safety & AI Integrity

  • DeceptionBench: A Benchmark for AI Deception in Real-world Scenarios Tests deceptive behavior across 150 scenarios; shows LLMs lie more under incentives, pressure, or multi-turn strategic framing. Read here.

Applied AI in Healthcare & Science

  • Multimodal LLM Pipeline for Clinical Trial Matching: A GPT-based pipeline that reasons over raw EHR text + medical imaging, achieving 93% benchmark accuracy and reducing screening time by 80%. Read here.

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We like real, practical, and tangible use-cases and hate hand-wavy, theoretical, and abstract concepts that don’t drive real-world outcomes.

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