TechCrunch

DECEMBER 26, 2021

Over the last two years, New Zealand’s startup scene has seen record venture and early-stage investment. Despite the pandemic, 2020 saw $158 million invested into 108 deals, representing the third year in a row of over $100 million in investment in startups. According to a PwC report, 2020 was also the third year of more than 20% year-over-year growth in dollars invested.

Film 268

Film Government Report Trends 268

Martin Fowler

DECEMBER 26, 2021

I listen to a lot of interesting music, so picked out my six favorite. new-to-me albums this year. I hope you find something interesting to groove to in there.

199

199

The Daily WTF

DECEMBER 26, 2021

Per tradition, we're taking the week before the new year as a chance to review some of our favorites from this year. We open with this one from way back in January. Consider it… a gift. Tyra was standing around the coffee maker with her co-workers when their phones all dinged with an email from management. Edgar is no longer employed at Initech.

Software Review 98

Software Review Technical Review Weak Development Team Testing 98

Netlify

DECEMBER 26, 2021

Throughout December we’ll be highlighting a different Netlify feature each day. It might just be the thing you need to unlock those creative juices, and dust off that domain you registered but never deployed! Keep an eye on the blog and on Twitter for each feature! On engineering teams and in life, in general, time tends to be the most valuable yet least plentiful resource.

Resources 52

Resources Study Testing Engineering 52

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

Artificial Inteligence

Trigent

DECEMBER 26, 2021

QA for AI/ML applications requires a different approach when compared to traditional applications. Unlike the latter that has set business rules with defined outputs, the continuously evolving nature of AI models makes their outcomes ambiguous and unpredictable. QA methodologies need to adapt to this complexity and overcome issues relating to comprehensive scenario coverage, lack of security, privacy, and trust. .

Applications 52

Applications Data Testing Training 52