Biotechnologist Sebastian Cocioba uses gene-editing to create new kinds of flowers from his home lab on Long Island, aiming to democratize genetic engineering.
The article from WIRED introduces Sebastian Cocioba, a biotechnologist who conducts plant engineering from his home lab on Long Island. Cocioba's journey in plant biotechnology began in his childhood with a fascination for plants, which later transformed into a passion for genetically modifying flowers to create novel varieties. Despite facing financial and academic challenges, Cocioba built a makeshift laboratory by acquiring equipment and using 3D printing to create affordable tools. His goal is to democratize the tools of genetic engineering and make them more accessible to amateurs. He documents his experiments online and sells plasmids used for flower transformation. Cocioba also collaborates with startups like Senseory Plants, aiming to engineer plants that emit unique scents, such as the aroma of old books, thereby redefining the indoor plant experience.
The article from WIRED introduces Sebastian Cocioba, a biotechnologist who conducts plant engineering from his home lab on Long Island. Cocioba's journey in plant biotechnology began in his childhood with a fascination for plants, which later transformed into a passion for genetically modifying flowers to create novel varieties. Despite facing financial and academic challenges, Cocioba built a makeshift laboratory by acquiring equipment and using 3D printing to create affordable tools. His goal is to democratize the tools of genetic engineering and make them more accessible to amateurs. He documents his experiments online and sells plasmids used for flower transformation. Cocioba also collaborates with startups like Senseory Plants, aiming to engineer plants that emit unique scents, such as the aroma of old books, thereby redefining the indoor plant experience.
AI integration will transform business structures, shifting from hierarchical to more fluid project-based models, enabling organizations to leverage human and artificial intelligence synergistically.
The article discusses the need for more efficient and cost-effective AI models to promote widespread innovation, critiquing the current expensive approach taken by big tech companies in the pursuit of AGI.
- There's a costly arms race among big tech companies to create the most powerful AI models.
- This high cost is limiting innovation because smaller players can't afford to use these models.
- The author suggests focusing on creating lighter, cheaper models that are almost as good as the top ones.
- The cost of using these models is decreasing rapidly, making it more feasible for startups to create AI apps.
- By prioritizing cost-effectiveness, we can democratize AI and foster a thriving ecosystem of AI applications
- There's a costly arms race among big tech companies to create the most powerful AI models.
- This high cost is limiting innovation because smaller players can't afford to use these models.
- The author suggests focusing on creating lighter, cheaper models that are almost as good as the top ones.
- The cost of using these models is decreasing rapidly, making it more feasible for startups to create AI apps.
- By prioritizing cost-effectiveness, we can democratize AI and foster a thriving ecosystem of AI applications
Ecosia and Qwant are developing a web index for Europe to challenge the dominance of Google and Bing.
The FIDO Alliance's new Passkey standard aims to make password-less authentication a reality, but the real challenge lies in getting users to adopt the technology.
