5 Non-LLM Software Trends To Be Excited About
- Leonardo Creed tl;dr: “It’s true that LLMs are revolutionary, and while I work with LLMs daily, there are so many other things that are fascinatingly progressing. I go over some topics below and provide a host of links for each topic for those interested in learning more. I see these topics as trends that are only growing as time goes on.”featured in #566
The Slow Evaporation Of The Free / Open Source Surplus
- Baldur Bjarnason tl;dr: Baldur argues we’ve been in a FOSS surplus due to the software industry’s high margins and wealth created by engineers, allowing both companies and individuals to invest in open source. “The derived FOSS surplus generates billions, if not trillions, of dollars of value for the economy and most of the costs – cost of creation, opportunity cost, and the cost of OSS competing with your more lucrative proprietary products – is absorbed by the makers.”featured in #546
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Top 18 Products Launched With Speech AI
- Jesse Sumrak tl;dr: Whether you're a developer, founder, or product innovator, these fast-growing products are shaping the Speech AI space and demonstrating the endless possibilities unlocked by this technology.featured in #534
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The One About The Web Developer Job Market
- Baldur Bjarnason tl;dr: (1) Finding a non-bullshit job is likely only going to get harder. (2) The overall developer job market will continue to fluctuate, but without dramatic change there isn’t much on the horizon that seems likely to turn the decline around. (3) Finding effective documentation, information, and training is likely to get harder, especially in specialised topics where LLMs are even less effective than normal.featured in #500
What I Learned From Looking At 900 Most Popular Open Source AI Tools
- Chip Huyen tl;dr: I think of the AI stack as consisting of 4 layers: (1) Infrastructure: Toolings for serving, vector search and database. (2) Model development: Toolings for developing models and anything that involves changing a model’s weights. (3) Application development with readily available models. This is the layer that has seen the most actions in the last 2 years and is still rapidly evolving. (4) Applications: Most popular types of applications are coding, workflow automation, information aggregation.featured in #499
The Demise Of Coding Is Greatly Exaggerated
- Murat Demirbas tl;dr: “Natural language is ambiguous and not suitable for programming. LLMs still need to generate code to get things done. If not inspected carefully, this incurs tech debt at monumental speed of the computers. The natural language prompts are not repeatable/deterministic, they are subject to breaking any time. This makes "natural language programming" unsuitable for even small sized projects, let alone medium to large projects.” Murat also believes that certain tasks require too much expertise to be completed by an LLMs as they stand.featured in #498
Meta's New LLM-Based Test Generator Is A Sneak Peek To The Future Of Development
- Leonardo Creed tl;dr: “Meta claims that this “this is the first paper to report on LLM-generated code that has been developed independent of human intervention (other than final review sign off), and landed into large scale industrial production systems with guaranteed assurances for improvement over the existing code base.” Furthermore, there are solid principles that developers can take away in order to use AI effectively themselves.”featured in #492
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