VC funding is not a guarantee of success and may actually indicate a company's inability to be profitable on its own.
Taking VC funding means selling a part of your company and changing the objective from building a company you like to building a company that can be sold for a higher price in the future.
VC funding can lead to second-order effects such as hiring more employees than desired, spending time looking for new investors instead of building the company, and prioritizing growth over profitability.
The author argues that raising money from venture capitalists (VCs) puts startups on a defined path with limited outcomes: failure, acquisition, or going public.
The most important thing is to consider one's goals and the specific circumstances of the company when deciding whether or not to take VC funding.
VC funding can distort incentives and hinder a company's vision by prioritizing growth and profit over other goals.
The author explores how small a .NET Hello World binary can be in terms of file size while still functioning as a normal executable on a Windows machine.
The author sets up arbitrary rules for the experiment, such as using a managed entry point implemented in C# or CIL, running on .NET Framework 4.x.x, and not using any third-party dependencies.
Through various optimizations and manual code crafting, the author successfully reduces the file size of the Hello World binary to 834 bytes, achieving a minimal size.
This article discusses the potential dangers of using Large Language Models (LLMs) and the need for a secure LLM supply chain with model provenance to ensure AI safety.
It shows how an open-source model, GPT-J-6B, can be modified to spread misinformation while remaining undetected by standard benchmarks.
The article introduces AICert, an upcoming open-source tool that will provide cryptographic proof of model provenance, addressing the need for traceability and accountability in the AI industry.
Users of InfluxDB Cloud in Belgium experienced issues with missing or incomplete data on their dashboards.
It was discovered that there was a discontinuation of AWS ap-southeast-2 (Sydney) and GCP europe-west1 (Belgium) regions, which may have caused the data problems.
Some users did not receive emails from InfluxDB notifying them of this change.
InfluxDB Cloud shut down in Belgium without proper notification, causing data loss for some users.
Users express frustration about the lack of effective communication methods used by InfluxDB.
Suggestions for better notification methods include flash messages, no new resource creation, emails, earlier service end date, aggressive contact attempts, and the option for users to export or move their data before deletion.
The author has developed a website called ShadeMap that simulates tree shadows using LiDAR data.
Radar, which is commonly used for shadow simulation, misses 90% of the shadows cast by trees because it only reflects off the ground.
LiDAR, on the other hand, reflects off all objects and provides a much richer model of the earth's surface, making it more accurate for shadow simulation. However, collecting LiDAR data is time-consuming and expensive.
Radar does not include vegetation in its mapping because it reflects off the ground, making objects like trees and buildings invisible.
The Shuttle Radar Topography Mission (SRTM) uses radar that does penetrate into some canopies, but it didn't capture foliage or building shadows in its data.
Lidar can be used to map tree shadows with granular detail and has various potential applications such as solar panel placement, photography, car parking, and more.
Comedian Sarah Silverman and authors Christopher Golden and Richard Kadrey are suing OpenAI and Meta for copyright infringement, alleging that the companies trained their AI models on illegally-acquired datasets containing their works without their consent.
The lawsuits claim that OpenAI's ChatGPT and Meta's LLaMA summarized the books of the plaintiffs when prompted, infringing on their copyrights.
The authors are seeking statutory damages, restitution of profits, and more, and the lawsuits challenge the limits of copyright in the AI industry.
Sarah Silverman is suing OpenAI and Meta for copyright infringement, claiming that they have used copyrighted works without permission in their AI training datasets.
This lawsuit brings attention to the debate surrounding copyright and fair use in the AI community.
The case questions the accuracy of OpenAI's ChatGPT's summaries, raises concerns about the legality of using copyrighted material in training AI models, and may have implications for the use of copyrighted content in AI training datasets.
The education system in California is facing challenges in teaching mathematics effectively.
There is a movement to water down math education in California, including banning algebra in 8th grade and replacing it with "data science" courses.
These policy changes have been criticized for being ineffective and detrimental to students, and experts argue that a stronger foundation in math, including algebra, is necessary for success in STEM fields.
The article discusses the failure of large institutions, including schools, in effectively fostering learning and growth and suggests that misaligned incentives contribute to this.
The conversation delves into the impact of culture, parenting, and socioeconomic factors on educational outcomes, as well as the potential negative effects of extrinsic motivation on intrinsic motivation and creativity.
The need for a more comprehensive and thoughtful approach to education reform, considering unintended consequences and student demographics, is emphasized.
In a world where people are constantly obsessed with new tools and technologies, true mastery and skill are what matter most, not the tools themselves.
The success and greatness of a person in any industry are not defined by the latest software or hardware they use, but by their mindset, skill, and deep understanding of their craft.
Pros understand the importance of consistently practicing and honing their skills, regardless of the tools available, and they prioritize timeless principles over fleeting trends.
Professionals understand the importance of choosing the right tools for their needs and prioritize problem-solving skills over specific tools or languages.
Mastery in any craft comes from understanding how to use tools effectively for multiple purposes and continuously learning their nuances.
Amateurs often focus on collecting new tools rather than developing fundamental skills and may get caught up in the hunt for the latest and greatest tools.
Perl revolutionized text manipulation and programming by combining them into one system, replacing the need for separate C, awk, sed, and shell commands.
Perl improved code maintainability and streamlined complex text processing tasks, offering a more capable alternative for larger tasks compared to the Unix philosophy of composing small tools.
Despite the rise of languages like Python and Ruby, Perl is still widely used and has a dedicated community due to its comprehensive ecosystem, robust Unicode support, and powerful regular expressions for text manipulation.