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

AI browser bans and the top software flaws of 2025

AI browser bans and the top software flaws of 2025

This podcast episode dives into critical cybersecurity topics, starting with Gartner's warning to ban AI browsers in the workplace due to significant security risks, like zero-click exploits. The conversation then broadens to the role of AI model providers in the threat intelligence community, questioning their responsibility in sharing data after attacks. The panel also analyzes MITRE's latest list of top software weaknesses, the pros and cons of using social logins (SSO), and a novel 'bring-your-own-virtual-machine' attack vector that challenges traditional endpoint security.

Context Engineering 2.0

Context Engineering 2.0

Simba Khadder explains the evolution of feature stores and MLOps, detailing why they remain crucial in the age of LLMs for high-scale use cases. He discusses the acquisition of his company, Featureform, by Redis and outlines their new vision: building a "Context Engine" for AI. This engine aims to unify structured data, unstructured data, and memory into a single pane of glass, moving beyond simple RAG to a more sophisticated "Context Engineering 2.0" that empowers agents with rich, queryable context.

The future of intelligence | Demis Hassabis (Co-founder and CEO of DeepMind)

The future of intelligence | Demis Hassabis (Co-founder and CEO of DeepMind)

Google DeepMind CEO Demis Hassabis discusses the path to AGI, focusing on the scientific frontiers of the next decade. He covers the importance of solving 'root node' problems like fusion energy, the challenge of 'jagged intelligence' in current models, and the promise of world models and simulations like Genie and SimA. The conversation also explores the balance between scientific rigor and commercial competition, and the profound societal and philosophical questions AGI will force us to confront.

Why Physical AI Needs a new Data Set | Rerun CEO

Why Physical AI Needs a new Data Set | Rerun CEO

Nikolaus West, CEO of Rerun, explains how their data logging and visualization platform, built on an Entity Component System (ECS) inspired by gaming, is unlocking new capabilities in physical AI. He discusses the rapid progress in robot manipulation through imitation learning, the gap between impressive demos and real-world products, and the critical need for better data tooling to handle complex, multi-rate sensor data in robotics and AR/VR.

Fundamentals of Data Engineering • Matt Housley & Joe Reis

Fundamentals of Data Engineering • Matt Housley & Joe Reis

Joe Reis and Matt Housley, authors of "Fundamentals of Data Engineering," discuss how AI has transformed data engineering practices since their book's release. They emphasize the enduring importance of foundational knowledge, the challenges AI poses for junior engineers, and the critical balance between leveraging AI assistance and maintaining core expertise in an increasingly complex field.

Flexible Orchestration for AI & ML: Beyond Kubernetes Automation

Flexible Orchestration for AI & ML: Beyond Kubernetes Automation

Explore the concept of flexible workload orchestration as a unified solution to manage diverse application types, from traditional web services to complex AI/ML pipelines. This approach simplifies operations, breaks down tooling silos, and provides a future-proof infrastructure for evolving AI technologies.

← PreviousNext →

Stay In The Loop! Subscribe to Our Newsletter.

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