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☁️ Luis Herrera 🚀
The problem with computers is all they can do is provide answers (Picasso)
Luis Herrera is a Solutions Architect currently working at Redis Labs, a company that provides in-memory databases and caching solutions. With an extensive technical background, Luis has proven to be a valuable asset to the company by developing complex solutions to meet clients' needs. Before joining Redis Labs, Luis worked in multiple IT roles where he gained experience working with cloud infrastructure, architecture, database administration, and software development. Luis's expertise in these areas has allowed him to remain up-to-date with the latest technologies and industry trends, providing valuable insights to the company's clients. Luis is also an excellent communicator and enjoys collaborating with colleagues to identify new opportunities and create innovative solutions.
Highlights
Leyendo el interesante articulo de Alex Rayón Jerez “La inteligencia artificial no puede ser neutra”. arguments que los datos no son un recurso natural como el petróleo, sino un recurso cultural profundamente ligado a la actividad humana. Esto significa que los datos están cargados de significados, valores y sesgos que reflejan las culturas y sociedades que los generan. A diferencia de un recurso natural, los datos no existen por sí mismos, sino que son producidos y utilizados en contextos sociales específicos, lo que implica riesgos como la reproducción de desigualdades y problemas de propiedad intelectual. La inteligencia artificial, al basarse en estos datos, no puede ser neutra, ya que está inevitablemente influenciada por las decisiones y voluntades humanas.
Reading Alex Rayón Jerez's interesting article, "Artificial Intelligence Cannot Be Neutral," he argues that data is not a natural resource like oil, but rather a cultural resource deeply connected to human activity. This means that data is imbued with meanings, values, and biases that reflect the cultures and societies that generate it. Unlike a natural resource, data does not exist independently; it is produced and utilized within specific social contexts, which introduces risks such as the reproduction of inequalities and intellectual property issues. Since artificial intelligence relies on this data, it cannot be neutral, as it is inevitably influenced by human decisions and intentions.
https://lnkd.in/dzJNA_fq
Not everyone wants to rely on LLMs inference served over a public API. Running LLMs locally has its advantages: enhanced privacy, reduced latency, cost savings, greater customization, data sovereignty, and the ability to avoid censorship. These benefits make it a compelling choice for many applications, from enhancing customer interactions to driving innovation in various industries.
Unlock the full potential of #genAi and #LLMs on any device. Discover how TorchChat, an innovative open-source library just released by PyTorch's team, is torching through the limitations of API dependence by reducing LLMs' size to serve them locally in the most optimal way. Dive into the article and see how #TorchChat is enabling powerful local inference for everyone, bringing high-performance LLMs to your servers, desktops, and mobile devices.
