But this year, whether to foster developer goodwill or advance its ecosystem ambitions (or both), Google debuted a number of open-source tools primarily aimed at supporting generative AI projects and infrastructure.
Beyond MaxDiffusion, Google’s launching Jetstream, a new engine to run generative AI models — specifically text-generating models (so not Stable Diffusion).
“We’ve heavily optimized [the models’] performance on TPUs and also partnered closely with Nvidia to optimize performance on large GPU clusters,” Lohmeyer said.
The goal is to reduce the barrier to entry for getting generative AI models onto TPU hardware, according to Google — in particular text-generating models.
And Optimum TPU doesn’t yet support training generative models on TPUs — only running them.
The Open Source Robotics Foundation (OSRF) this week announced the launch of the similarly named Open Source Robotics Alliance (OSRA).
The new initiative is designed to maintain development for and maintenance of open source robotics projects, with a particular focus on the OSRF’s own robot operating system (ROS).
First released in 2007 by erstwhile Bay Area incubator Willow Garage, ROS has played a foundational role in robotics development for decades.
In a show of support, Nvidia and Qualcomm have both signed on as “Platinum” members for the new alliance, along with Alphabet’s X spinout Intrinsic.
Former Open Robotics CEO Brian Gerkey (who current serves as Intrinsic’s CTO) has been appointed to the OSRA’s board of directors.
Elon Musk’s xAI released its Grok large language model as “open source” over the weekend.
But does releasing the code for something like Grok actually contribute to the AI development community?
This isn’t the first time the terms “open” and “open source” have been questioned or abused in the AI world.
So where does xAI’s Grok release fall on this spectrum?
Is his nascent AI company really dedicated to open source development?
The UK has exited the European Union, but semiconductor development is emerging as one of the areas where it hopes to partner for better economies of scale — and much-needed funding.
The UK itself said it would put up a more modest £35 million ($44 million) in funding for UK efforts over the next few years as part of that.
The Chips Joint Undertaking, for example, has an overall budget of about €11 billion from both public and private contributions.
In December 2023, Pragmatic Semiconductor, another Cambridge-based chip company, raised $231 million at a $500 million valuation.
“We are very happy to welcome the UK to the Chips Joint Undertaking as a participating state,” said Jari Kinaret, Chips JU Executive Director, in a statement.
It’s hard to keep track of crypto’s technical development, but one thing hasn’t changed much: blockchain applications are notoriously hard to build.
This stems in part from their decentralized nature, resulting in a lack of uniform standards across different infrastructure pieces.
Initia, founded by a group of developers in their late 20s, is trying to bring more interoperability to multi-chain networks and simplify the process of creating app-specific blockchains, or app chains.
In layman’s speak, Initia is abstracting away app chains’ technical complexity, aiming to make them more friendly to both end users and app developers.
They paused the project after the FTX implosion and eventually changed tack to work on blockchain infrastructure.
Rashida Richardson, senior counsel, AI at MastercardBriefly, how did you get your start in AI?
On the second point, law and policy regarding AI development and use is evolving.
How can investors better push for responsible AI?
Investors can do a better job at defining or at least clarifying what constitutes responsible AI development or use, and taking action when AI actor’s practices do not align.
Currently, “responsible” or “trustworthy” AI are effectively marketing terms because there are no clear standards to evaluate AI actor practices.
Enterprises need to understand how much to budget into AI tools, how to weigh the benefits of AI versus new recruits, and how to ensure their training is on point.
A recent study also found that who is using AI tools is a critical business decision, as less experienced developers get far more benefits out of AI than experienced ones.
At Waydev, we’ve spent the past year experimenting on the best way to use generative AI in our own software development processes, developing AI products, and measuring the success of AI tools in software teams.
This is what we’ve learned on how enterprises need to prepare for a serious AI investment in software development.
Then use an engineering management platform (EMP) or software engineering intelligence platform (SEIP) to track whether your adoption of AI is moving the needle on those variables.
Look at your startup’s CAC to decide if you should launch another productUntil recently, it was widely accepted that startups, constrained by limited resources, should primarily concentrate on a single product.
Investing in customer acquisition is justified when the net present value of the profits from the acquisition exceeds the customer’s customer acquisition cost (CAC).
Customer acquisition and product development stand out as a startup’s most important investments.
Customer acquisition and product development stand out as a startup’s most important investments.
With the rise in CAC, the relative value of customer acquisition remains the same compared to new product development.
The Space Development Agency is the mystery customer behind Rocket Lab’s up-to $515 million, 18-satellite order announced in late December, the two firms announced today.
In a regulatory filing from December 21, Rocket Lab said it would “design, manufacture, deliver and operate 18 space vehicles” for an unnamed U.S. government customer.
Under the contract, Rocket Lab will deliver and operate a prototype constellation in two orbital planes of nine satellites each.
Rocket Lab will not be providing the communications payload, and company executives declined to name that provider during a press release Monday.
“We welcome Rocket Lab as the newest member of Team SDA and our third performer on the T2TL- Beta program,” said Derek Tournear, SDA director.
Simultaneously, developers and the wider DevSecOps community must prepare to address four global trends in AI: the increased use of AI in code testing, ongoing threats to IP ownership and privacy, a rise in AI bias, and — despite all of these challenges — an increased reliance on AI technologies.
Successfully aligning with these trends will position organizations and DevSecOps teams for success.
From luxury to standard: Organizations will embrace AI across the boardIntegrating AI will become standard, not a luxury, across all industries of products and services, leveraging DevSecOps to build AI functionality alongside the software that will leverage it.
To prepare, organizations must invest in revising software development governance and emphasizing continuous learning and adaptation in AI technologies.
In our latest Global DevSecOps Report, 81% of respondents said they would like more training on how to use AI effectively.
