Category: Unite.AI

Evolution has been fine-tuning life at the molecular level for billions of years. Proteins, the fundamental building blocks of life, have evolved through this process to perform various biological functions, from fighting infections to digesting food. These complex molecules comprise long chains of amino acids arranged in precise sequences that dictate their structure and function.

According to Gartner, 30% of GenAI projects will likely be abandoned after proof-of-concept by the end of 2025. Early adoption of GenAI revealed that most enterprises’ data infrastructure and governance practices weren’t ready for effective AI deployment. The first wave of GenAI productization faced considerable hurdles, with many organizations struggling to move beyond proof-of-concept stages

Most AI training follows a simple principle: match your training conditions to the real world. But new research from MIT is challenging this fundamental assumption in AI development. Their finding? AI systems often perform better in unpredictable situations when they are trained in clean, simple environments – not in the complex conditions they will face

As 2024 comes to a close, we reflect on a year with hacks, outages, legislation, and rapidly emerging trends that shifted the cybersecurity landscape. Artificial intelligence (AI) continues to evolve at breakneck speed, with generative and agentic AI pushing organizations to consider its role across every aspect of the business. Meanwhile, new categories emerge to

Generative diffusion models like Stable Diffusion, Flux, and video models such as Hunyuan rely on knowledge acquired during a single, resource-intensive training session using a fixed dataset. Any concepts introduced after this training – referred to as the knowledge cut-off – are absent from the model unless supplemented through fine-tuning or external adaptation techniques like

The headlines tell one story: OpenAI, Meta, Google, and Anthropic are in an arms race to build the most powerful AI models. Every new release—from DeepSeek’s open-source model to the latest GPT update—is treated like AI’s next great leap into its destiny. The implication is clear: AI’s future belongs to whoever builds the best model.

Loris Degioanni is the Chief Technology Officer and Founder of Sysdig. He is also the creator of the popular open source troubleshooting tool, sysdig, and the open source container security tool Falco. Prior to founding Sysdig, Loris co-created Wireshark, the open source network analyzer, which today has 20+ million users. Sysdig is dedicated to ensuring

The hype surrounding AI remains prevalent in healthcare but is particularly strong in radiology. If you remember the early days of computer-aided design (CAD), it’s quite impressive how far the technology has come. A native of ChatGPT would perhaps contend that much work needs to be done before AI can reach its full potential in

If 2024 was the year of significant advancements in general AI, 2025 is shaping up to be the year of specialized AI systems. Known as vertical AI agents, these purpose-built solutions combine advanced AI capabilities with deep domain expertise to tackle industry-specific challenges. McKinsey estimates that over 70% of AI’s total value potential will come

The US Copyright Office just released their most significant guidance yet on AI and copyright. This report cuts through the confusion about who owns what when it comes to AI-created content. The law still centers on human creativity. The Copyright Office makes this crystal clear – copyright protection stems from human creative input, not from