Tokenless

Tokenless

Guardians of the State: An Air-Gapped AI Fortress for Consumer Data — Rachna Srivastava, DFPI

Interactive discovery

Explore the topic map

Follow the connections between themes, people, and ideas across the Tokenless archive in an interactive topic modeling map.

Open the map Browse posts

Machine Learning

View All
Guardians of the State: An Air-Gapped AI Fortress for Consumer Data — Rachna Srivastava, DFPI

Guardians of the State: An Air-Gapped AI Fortress for Consumer Data — Rachna Srivastava, DFPI

Rachna Srivastava discusses building a legally defensible AI system for financial fraud detection, emphasizing that generative AI has eroded traditional trust. Her team at DFPI engineered an offline, hardware-secured data pipeline using Kafka, Spark, and semantic routing to ensure explainability, reproducibility, and auditability. They implemented a one-way data diode for secure learning and Apache Iceberg for time-travel queries, asserting that "trust is a physical property" built into the system's core.

Invited Research Talk: Measuring Generalization in EEG Foundation Models

Invited Research Talk: Measuring Generalization in EEG Foundation Models

This talk presents a multi-dimensional evaluation and interpretability framework for EEG foundation models. It reveals that current models often fail to outperform supervised baselines for BCI tasks, lack robustness to sparse channels, and exhibit an aperiodic low-frequency bias, making them better at capturing subject-specific rather than task-specific information. The analysis highlights critical deficiencies and suggests future directions for pre-training objectives and data collection to improve generalization.

Can LLMs Write Fast Multi-GPU Kernels? — Simran Arora, Together AI

Can LLMs Write Fast Multi-GPU Kernels? — Simran Arora, Together AI

Simran Arora discusses the critical bottleneck shift in large AI workloads from GPU compute to inter-GPU communication. Her team's solution, ParallelKittens, offers a set of primitives to optimize multi-GPU kernels by leveraging fundamental transfer mechanisms and compute-communication overlapping. They introduce ParallelKernelBench, a benchmark to evaluate AI models' ability to generate such kernels, revealing that while models can handle syntax, they struggle with deeper reasoning about communication patterns and hardware trade-offs.

Artificial Intelligence

View All
AI-Native Organisations Run on Skills: How to Structure and Scale Them — Imad Touil, QuantumBlack

AI-Native Organisations Run on Skills: How to Structure and Scale Them — Imad Touil, QuantumBlack

Imad Touil explores the critical need for governing AI skills within organizations, asserting that skills represent the true repository of enterprise know-how. He contrasts simplified coding agent loops with complex, real-world product lifecycles, demonstrating how ungoverned skills lead to technical debt—including duplication, quality degradation, security risks, and lack of discoverability. Proposing a microservices-inspired approach, Touil outlines a centralized skills platform and human-led governance model essential for achieving deterministic workflows, boosting productivity, and mitigating risks in AI-native enterprises.

Your Code Has Bugs. Lean4 Has Proofs: Formal Verification for Engineers — Varun Pant, AWS

Your Code Has Bugs. Lean4 Has Proofs: Formal Verification for Engineers — Varun Pant, AWS

Varun Pant introduces formal verification as the solution to reliably validate AI-generated code, proposing a division where humans define specifications and machines handle code and proof. He details Lean's role as a unified language for code and proof, exemplified by an AI rewriting zlib with 32,000 lines of proof, and AWS's Cedar using Lean specs with Rust production code reconciled by 100 million nightly tests. The talk also covers deductive verification with solvers and future cross-language verification with Strata, aiming for "provably correct" software.

How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma

How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma

Figma's internal AI agent adoption journey faces challenges like reduced developer agency, skepticism from senior engineers, and communication inefficiency. Solutions include investing in verification, using a testing pyramid for agent review, prioritizing detailed planning over prompting, engaging skeptics to build AI safety roadmaps, and implementing attention-aware communication by clearly marking AI-generated content.

Technology

View All
Platform Engineering for Developers, Architects & the Rest of Us • Daniel Bryant • GOTO 2025

Platform Engineering for Developers, Architects & the Rest of Us • Daniel Bryant • GOTO 2025

Daniel Bryant discusses platform engineering for software developers and architects, emphasizing treating platforms as internal products with developers as customers. He outlines a three-layered architecture, the evolution from monolithic systems to microservices, and the importance of 'golden bricks' over 'golden paths' for composability. Key takeaways include API-first design, minimizing cognitive load, avoiding leaky abstractions, and measuring success through frameworks like DORA and DevEx to achieve speed, safety, and scale.

Modern Enterprise Architecture: Architecting for Outcomes • Simon Rohrer • GOTO 2025

Modern Enterprise Architecture: Architecting for Outcomes • Simon Rohrer • GOTO 2025

Simon Rohrer challenges traditional Enterprise Architecture (EA) principles, proposing a modern approach focused on outcomes, continuous evolution, and socio-technical alignment. He outlines five key tenets: Aligning Value, People & Technology; achieving Better Value Sooner, Safer, Happier; implementing Continuous Conversational & Automated Governance; scaling DevOps across the enterprise; and fostering Evolutionary Enterprise Architecture.

Elon's Former Battery Chief on Making Transformers 100x Smaller | Drew Baglino, Heron Power

Elon's Former Battery Chief on Making Transformers 100x Smaller | Drew Baglino, Heron Power

Drew Baglino, former Tesla Powertrain & Energy head and now CEO of Heron Power, reveals why the current electricity grid is inadequate for the explosive growth of AI data centers. He explains how Heron Power's wideband gap power semiconductors will revolutionize grid-to-chip infrastructure, cutting power losses by half, shrinking massive transformers by 100x, and transforming data centers into grid-positive assets for a more efficient and sustainable energy future.

Recent Post

Marc Andreessen: The US is in a AI Arms Race & It Decides The World's Future

Marc Andreessen: The US is in a AI Arms Race & It Decides The World's Future

Marc Andreessen and Joe Lonsdale discuss how AI and robotics present a pivotal opportunity to re-industrialize the United States, reversing decades of policy choices that led to slower growth and a deep urban-rural divide. They argue for a future focused on advanced manufacturing of robots and AI-powered hardware, tackling the 'cost disease' in healthcare and education, and rethinking policies on immigration and regulation to unlock the country's full potential.

The Cloud Native Attitude • Anne Currie & Sarah Wells

The Cloud Native Attitude • Anne Currie & Sarah Wells

Authors Anne Currie and Sarah Wells discuss the core principles of "The Cloud Native Attitude", defining it not as a specific technology stack but as a cultural mindset focused on removing bottlenecks and enabling rapid, iterative change. The summary covers the primacy of CI/CD, the evolution of orchestrators like Kubernetes, and how a cloud native approach is a critical enabler for building sustainable, green software.

911: The Future of Python Notebooks is Here — with Marimo’s Dr. Akshay Agrawal

911: The Future of Python Notebooks is Here — with Marimo’s Dr. Akshay Agrawal

Software developer Akshay Agrawal discusses Marimo, a next-generation reactive notebook for Python designed to solve the reproducibility and workflow issues inherent in traditional notebooks. He explains how Marimo's reactivity, developer-friendly design, and ability to transform into a data app create a seamless environment for exploration and deployment.

Dwarkesh and Noah Smith on AGI and the Economy

Dwarkesh and Noah Smith on AGI and the Economy

Dwarkesh Patel and Noah Smith debate the definition of AGI, its economic implications, and timelines. They contrast an economic definition (automating white-collar work) with a cognitive one, exploring why current models lack economic value despite reasoning abilities due to a failure in 'continual learning'. The discussion covers the potential for explosive economic growth versus a collapse in consumer demand, the substitution vs. complementarity of human labor, and the geopolitical shift from population size to inference capacity as the basis of power.

The Pathologies of Big "Messy" Data in Telco • Jay Fenton • YOW! 2015

The Pathologies of Big "Messy" Data in Telco • Jay Fenton • YOW! 2015

Jay Fenton discusses the challenges of "big messy data" in the telecommunications industry, highlighting how legacy systems fail to handle the scale and complexity. He presents a suite of modern tools, including Graphistry, IPython, and D3.js, for large-scale data visualization and analysis, advocating for a "human-computer symbiosis" to empower engineers in managing complex networks.

Full Workshop: Realtime Voice AI — Mark Backman, Daily

Full Workshop: Realtime Voice AI — Mark Backman, Daily

An in-depth look at building real-time, production-grade voice AI agents using the open-source Pipecat framework. This summary covers the core concepts of voice AI pipelines, the shift to speech-to-speech models like Gemini Live, and advanced techniques for managing latency, context, and turn-taking.

← PreviousNext →

Stay In The Loop! Subscribe to Our Newsletter.

Get updates straight to your inbox. No spam, just useful content.