I am on a voyage of discovery through prompting and prompting technologies because these are the critical interfaces between what we want (or roughly imagine we want) from AI, and AI’s ability to deliver. I have seen suggestions that any deficiencies today are a detail that will soon be overcome. I’m not so sure. Yes, prompting technology… Read More
Author: Bernard Murphy
From Prompts to Prompt Engineering to Knowing Ourselves
A Remote Touchscreen-like Control Experience for TVs and More
How do you control your smart TV? With a remote control of course, already quite capable since it allows voice commands to find a movie or TV show without needing all that fiddly button-based control and lookup. But there’s a range of things you can’t do that we take for granted on a tablet or phone screen. Point and click on an object,… Read More
Scaling Debug Wisdom with Bronco AI
In the business press today I still find a preference for reporting proof-of-concept accomplishments for AI applications: passing a bar exam with a top grade, finding cancerous tissue in X-rays more accurately than junior radiologists, and so on. Back in the day we knew that a proof-of-concept, however appealing, had to be followed… Read More
Neurosymbolic code generation. Innovation in Verification
Early last year we talked about state space models, a recent advance over large language modeling with some appealing advantages. In this blog we introduce neurosymbolic methods, another advance in foundation technologies, here applied to automated code generation. Paul Cunningham (GM, Verification at Cadence), Raúl Camposano… Read More
Arm Lumex Pushes Further into Standalone GenAI on Mobile
When I first heard about GenAI on mobile platforms – from Arm, Qualcomm and others – I confess I was skeptical. Surely there wouldn’t be enough capacity or performance to deliver more than a proof of concept? But Arm, and I’m sure others, have been working hard to demonstrate this is more than a party trick. It doesn’t hurt that foundation… Read More
The IO Hub: An Emerging Pattern for System Connectivity in Chiplet-Based Designs
In chiplet-based design we continue the march of Moore’s Law by scaling what we can put in a semiconductor package beyond the boundaries of what we can build on a single die. This style is already gaining traction in AI applications, high performance computing, and automotive, each of which aims to scale out to highly integrated … Read More
The Importance of Productizing AI. Everyday Examples
Keeping up with the furious pace of AI innovation probably doesn’t allow a lot of time for deep analysis across many use cases. However I can’t help feeling we’re sacrificing quality and ultimately end user acceptance of AI by prioritizing new capabilities over rigorous productization. I am certain that product companies do rigorous… Read More
Two Perspectives on Automated Code Generation
In engineering development, automated code generation as a pair programming assistant is high on the list of targets for GenAI applications. For hardware design obvious targets would be to autogenerate custom RTL functions or variants on standard functions, or to complete RTL snippets as an aid to human-driven code generation.… Read More
Cocotb for Verification. Innovation in Verification
This time let’s see if we can stir up some lively debate. Cocotb isn’t new but it is an interesting alternative to mainstream testing methodologies. Paul Cunningham (GM, Verification at Cadence), Raúl Camposano (Silicon Catalyst, entrepreneur, former Synopsys CTO and lecturer at Stanford, EE292A) and I continue our series … Read More
A Big Step Forward to Limit AI Power Demand
By now everyone knows that AI has become the all-consuming driver in tech and that NVIDIA GPU-based platforms are the dominant enabler of this revolution. Datacenters worldwide are stuffed with such GPUs, serving AI workloads from automatically drafting emails and summarizing meetings to auto-creating software and controlling… Read More
From Prompts to Prompt Engineering to Knowing Ourselves