The Open Source Initiative recently kicked off a multi-stakeholder process to define machine learning systems that can be characterized as “Open Source.” A long list of non-profit organizations, corporations and research groups came together to find a common understanding of “open” principles applied to artificial intelligence.
To a varying degree, most companies are competing on their ability to deliver business value through software and technology. Producing software faster and with higher quality leads to more value delivered. It’s as simple as that, and security teams must embrace this reality to be successful and to enable the business.
Stay-at-home orders during the Covid-19 pandemic spurred new cloud computing and remote-technology setups, increasing company exposure to hackers. As a result, some corporate cybersecurity chiefs are also taking on the leadership role for all of information technology. Oversight of both groups isn’t an easy line to walk.
In this series of online round tables, Evil Martians brings together industry experts on developer productivity to discuss the best practices for designing, building, growing, and promoting successful dev tools. In this episode, they explore specifics of financing strategies in regards to developer tools business.
Running a multi-cloud strategy where you use different cloud vendors for different workloads helps companies avoid vendor lock-in and lets them use the best-of-breed tools across different platforms. But each company connects to its services in different ways, forcing programmers to write three different sets of connectors. It’s expensive and time consuming
If you follow the headlines, AI coding assistants such as GitHub Copilot and other large-language model (LLM)-based tools seem like the future of software development. But will prompting and generated code replace the day-to-day business of writing net-new code for software engineers?
One challenge for founders scaling an OSS company is that traditional enterprise SLAs do not seem to apply. The result is often a tangled web of multi-layered custom contracts, brittle or orphaned tracking systems, and professional service stop gaps. How can early stage founders avoid taking on more liability than they can handle?
Artificial intelligence (AI) and large language models (LLM) are changing users' expectations of software in ways that profoundly impact product strategy. This virtual conference will explore how AI and LLMs are creating new opportunities and even new business models for software in order to prepare you for the next generation of AI driven software.