Tokenless

Tokenless

a16z Goes Global: Why American Tech Must Lead the World

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
Frontier results, on device - RL Nabors, Arize

Frontier results, on device - RL Nabors, Arize

RL Nabors discusses the significant costs associated with using frontier AI models, covering security, latency, and financial implications. She introduces a framework for right-sizing AI solutions by leveraging smaller, task-specific models and Small Language Models (SLMs). The framework details how to prove task feasibility, establish success criteria with golden datasets, conduct capability evaluations (using tools like Phoenix), and select the most appropriate "Small And Good Enough" (SAGE) model. Nabors further demonstrates how prompt engineering, particularly few-shot prompting, and post-processing can close performance gaps with larger models, while advocating for continuous regression evaluations to maintain performance integrity. The overarching message is to "prototype big, deploy small" to optimize AI deployments.

Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

Research to Reality: Bringing Frontier ML Research to Production - Vaidas Razgaitis, Higharc

Vaidas Razgaitis, Senior Research Engineer at Higharc, shares three tactical tips to accelerate the transition of novel AI/ML research into production-ready features. He emphasizes addressing the critical handoff challenge between ML researchers and software engineers through structured documentation (Research Prototype Taxonomy Document), a well-organized monorepo utilizing decoupled microservices, and a systematic approach to code decomposition and PR review. These strategies aim to improve legibility, maintainability, and delivery speed for ML-driven products.

Uncertainty-Guided Data Augmentation for Engineers | Deep Dive - Yongmin Kwon

Uncertainty-Guided Data Augmentation for Engineers | Deep Dive - Yongmin Kwon

This session details a data-efficient method for training engineering surrogate models by using uncertainty quantification (UQ) to guide geometric data augmentation. Instead of random deformations, the approach lets the deep ensemble model identify its own knowledge gaps (epistemic uncertainty), then uses Free-Form Deformation (FFD) to generate new shapes specifically in those uncertain regions. This ensures every expensive simulation run yields maximally informative data, significantly improving model accuracy for a fixed computational budget across domains like structural mechanics and aerodynamics.

Artificial Intelligence

View All
a16z Goes Global: Why American Tech Must Lead the World

a16z Goes Global: Why American Tech Must Lead the World

This discussion explores a16z's expanding international strategy, emphasizing technology's pivotal role in economic growth and national security. The panel delves into why America's tech leadership is crucial globally, how AI is redefining government-private sector relationships, and the drive for countries to adopt frontier technologies while building local innovation ecosystems. Key topics include AI infrastructure, cybersecurity, defense tech, global startup expansion, and the elements of enduring tech ecosystems, highlighting trusted partnerships and the importance of Western technology.

GPT-5.6 Sol, FIFA AI & Wall Street’s AI nerves

GPT-5.6 Sol, FIFA AI & Wall Street’s AI nerves

OpenAI's new GPT-5.6 Sol model sparks debate on AI safety and release strategies, while Wall Street expresses growing skepticism over the long-term economics of frontier AI models. The discussion also touches on AI's impact on the FIFA World Cup and a thought-provoking paper comparing LLM anthropomorphism to Age of Empires II "goats."

The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI

The Prompt Is Still a Punch Card - Ted Johnson, JoinIn AI

Ted Johnson argues that current AI interfaces, particularly prompting, operate on an outdated "batch processing" protocol akin to punch cards. Despite advanced LLM capabilities, this interface design forces humans to adapt to machines, hindering natural interaction. He advocates for a shift towards human-compatible interfaces where AI actively participates in real-time conversation, leveraging its intelligence to remove user burdens and amplify human potential.

Technology

View All
Are Your Tests Slowing You Down? • Trisha Gee • GOTO 2025

Are Your Tests Slowing You Down? • Trisha Gee • GOTO 2025

Trisha Gee delivers a compelling talk on Developer Productivity Engineering (DPE) for testing, dissecting common pain points in writing, troubleshooting, and running tests. She advocates for strategic use of IDEs, advanced tooling like build caches and predictive test selection (leveraging ML), and a disciplined approach to test design to overcome these challenges, emphasizing that good tests serve as crucial living documentation.

The new post-quantum cryptography executive order. Plus: What is Q-Day, really?

The new post-quantum cryptography executive order. Plus: What is Q-Day, really?

This episode delves into Q-Day, the anticipated future when quantum computers can break public key cryptography, and the U.S. Executive Order accelerating the transition to post-quantum cryptography. Experts discuss why Q-Day is a gradual process rather than a sudden event, the critical importance of "crypto-agility" as a long-term strategy, and the necessity for organizations to begin immediate discovery and planning to secure data against "collect now, decrypt later" threats. The discussion also touches upon the broader, transformative benefits of quantum computing beyond just security.

Plenary Talk 3​: Challenges and research opportunities for global hyperscale services

Plenary Talk 3​: Challenges and research opportunities for global hyperscale services

Jim Kleewein's talk outlines the immense challenges and critical research opportunities in building and operating global hyperscale services like Microsoft 365 and Azure. He emphasizes that at this scale, traditional approaches fail, necessitating a "new golden age of applied research" across areas like continuous availability, data management, security, and sustainability. Kleewein also discusses AI's powerful but limited role, stressing the ongoing need for human expertise, and highlights the ethical imperative to prevent failures that can have life-or-death consequences.

Recent Post

Fine-Tuned Models Are Getting Out of Hand

Fine-Tuned Models Are Getting Out of Hand

A deep dive into how fine-tuned Small Language Models (SLMs) and RAG systems can be combined to create personalized AI agents that learn user-specific workflows, emulate decision-making, and collaborate with humans, moving beyond conversational interfaces to direct action within enterprise environments.

Sacks, Andreessen & Horowitz: How America Wins the AI Race Against China

Sacks, Andreessen & Horowitz: How America Wins the AI Race Against China

David Sacks details the Trump administration's strategy for AI and crypto, focusing on unleashing permissionless innovation, combating regulatory capture, and winning the global AI race through infrastructure and open source, while warning against the rise of "Orwellian AI."

Building Software That Survives • Michael Nygard & Charles Humble • GOTO 2025

Building Software That Survives • Michael Nygard & Charles Humble • GOTO 2025

Michael Nygard, author of 'Release It!', discusses his experiences at Sabre and Nubank, offering deep insights into balancing autonomy and centralization, the practical implications of Conway's Law, and how architectural boundaries can reduce organizational friction and the need for constant alignment.

Why Humans Are Still Powering AI [Sponsored]

Why Humans Are Still Powering AI [Sponsored]

AI's "dirty secret" is its deep reliance on human intelligence. Phelim Bradley, CEO of Prolific, explains how his platform provides the critical human data infrastructure for training and evaluating frontier models, emphasizing the shift from commoditized labor to a sophisticated marketplace of verified expertise.

The woman behind Canva shares how she built a $42B company from nothing | Melanie Perkins

The woman behind Canva shares how she built a $42B company from nothing | Melanie Perkins

Melanie Perkins, co-founder and CEO of Canva, shares the core philosophies that propelled the company to a $42 billion valuation. She details her 'Column B' thinking—building towards a dream future rather than from existing constraints—and explains how setting 'crazy big goals' and systematically learning from over 100 investor rejections were crucial. Perkins also discusses surviving a two-year technical rewrite without shipping features and Canva's foundational 'two-step plan' to build a valuable company and use its wealth to do the most good possible.

20+ Years in Tech: Things We Wish We Knew Sooner • Daniel Terhorst-North & Kevlin Henney

20+ Years in Tech: Things We Wish We Knew Sooner • Daniel Terhorst-North & Kevlin Henney

In a reflective and forward-looking conversation, Daniel Terhorst-North and Kevlin Henney explore the evolution of software development over the past 20 years and predict the key challenges and innovations for the next 20. They delve into the philosophy of programming language design, the critical need for hardware-sympathetic programming, the untapped potential of concurrency models like CSP and the Actor Model, and the future of user interfaces and decentralized technology.

← PreviousNext →

Stay In The Loop! Subscribe to Our Newsletter.

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