Hello and welcome to Sync #500!
First of all, Happy New Year! Secondly, this is the 500th issue of Sync. Such a milestone offers a chance to reflect on nearly 10 years of writing a weekly newsletter and to look ahead to the future, which I’ll be sharing with you soon in a separate post.
In this 500th issue, we’ll take a closer look at OpenAI’s proposed new corporate structure, the reactions it has sparked, and its potential impact on the tech world.
In other news, Nvidia is already eyeing the next big thing after AI—robotics. Meanwhile, Google CEO Sundar Pichai has urged employees to prepare for a transformative 2025. We also have a comparison between ChatGPT Search and Google Search, an overview of how AI performed in the recently concluded Advent of Code 2024, and an analysis of the state of AI hardware startups.
Over in robotics, Figure AI has shipped its first humanoid robots to a paying customer, and BYD has entered the humanoid robotics race.
We’ll conclude this week’s issue with a look at what to expect from mRNA vaccines in 2025 and with a company promising to bring underwater habitats—where people can live and work tens or hundreds of metres below the surface—a step closer to reality.
Enjoy!
The last three years have been a time of massive growth for OpenAI. The AI lab went from a startup known primarily within the tech and AI community into a poster child of the current AI boom.
However, such massive growth requires massive transformation. OpenAI is no longer the same company that released ChatGPT in November 2022 as an experiment. The company’s leadership has changed. Many key people, such as Mira Murati, former CTO, and Ilya Sutskever, co-founder and former chief scientist, left the company. Meanwhile, hundreds of new employees have joined, all contributing to a shift in the company’s culture and priorities.
Over the years, OpenAI has changed. Now, facing new challenges as a leader in the AI space valued at $157 billion, OpenAI proposes to change itself once again. However, OpenAI is going against some powerful forces that could prevent its plans from happening.
OpenAI began as a non-profit organisation, founded in 2015 with the goal of ensuring that artificial general intelligence (AGI) benefits all of humanity. However, OpenAI’s leadership realised that the nonprofit structure, which reflected the altruistic spirit and ideals behind its creation, was incompatible with the goal of building AGI.
The research and development of advanced AI models require an enormous amount of computing power—first to train the models and then even more to deploy them at scale to millions of users (OpenAI has 300 million weekly users). A non-profit organisation was not attractive to investors, who seek returns on their investments. Consequently, OpenAI began exploring ways to transform itself into a for-profit company.
Email conversations revealed by both Elon Musk’s legal team and OpenAI indicate that discussions about transforming OpenAI into a for-profit company began as early as 2017. In 2019, OpenAI announced a new corporate structure in which a for-profit entity (“OpenAI LP”) is controlled by a non-profit board, with capped profit-sharing for investors and employees. This rather unusual hybrid corporate structure represents a compromise between the harsh reality that a tech company needs to operate as a for-profit entity to attract investments and the nonprofit model that embodies OpenAI’s original spirit.
The capped-profit structure served OpenAI well. It made the company more attractive to investors, who poured over $20 billion into it, including half of that amount secured in October 2024 ($6.6 billion from a Series B funding round and $4 billion borrowed from banks). This approach paved the way for ChatGPT and the current AI boom we are experiencing today.
However, those billions raised for building AGI are not enough. Reports published in the summer of 2024 revealed that OpenAI was on track to lose approximately $5 billion that year. The investments needed for the research and development of new models, as well as securing the computing power required to train and deploy them—whether through renting or building dedicated data centres—will demand even more resources and many more billions of dollars.
To address these challenges and position itself for a successful future, OpenAI plans to once again change its corporate structure.
OpenAI has announced its intention to transition its for-profit arm into a Delaware Public Benefit Corporation (PBC) by 2025. “As we enter 2025, we will have to become more than a lab and a startup — we have to become an enduring company,” states OpenAI.
According to OpenAI, the PBC model is the solution to balancing shareholder interests, stakeholder priorities, and public benefits in its decision-making, potentially offering a middle ground between traditional for-profit goals and its founding mission.
Unlike traditional for-profit companies, which are solely focused on maximizing shareholder value, PBCs are legally required to balance profit-making with its stated public benefit. For OpenAI, this means ensuring that its mission of advancing AI to benefit all humanity remains central to its operations, even as it raises capital and grows its business.
The for-profit entity will adopt a PBC structure, allowing OpenAI to raise capital with conventional equity terms while maintaining a commitment to public benefit. The non-profit will retain significant equity in the PBC, providing it with substantial resources to fund charitable initiatives in sectors like health care, education, and science. The non-profit’s influence will shift away from controlling the for-profit to focusing on its charitable initiatives and ensuring that OpenAI’s mission of benefiting humanity remains central.
OpenAI plans, however, have been met with criticism and opposition.
Critics argue that OpenAI’s new corporate structure will prioritise investors and revenue over the company’s original mission of building AIG that benefits all of humanity. Others raised concerns that the transition could exploit non-profit tax benefits while operating as a for-profit entity.
The strongest opposition to OpenAI’s plans comes from Elon Musk. Musk, one of OpenAI’s founders and a significant financial supporter in its early days, left the organisation in 2018 due to differences in visions for its direction and priorities. Since the release and subsequent success of ChatGPT, Musk has become a vocal critic of OpenAI.
In March 2024, Musk filed a lawsuit against OpenAI and its leadership, claiming that the organisation has strayed from its original non-profit mission of advancing AI for public benefit by prioritising profit through its collaboration with Microsoft. Musk argues that this shift undermines OpenAI’s commitment to open-source development and public welfare. The lawsuit seeks to realign OpenAI with its founding principles—a move which, if successful, would effectively end OpenAI as we know it today and dramatically limit its funding options.
Although Musk calls in the lawsuit for OpenAI to return to its non-profit roots, it is worth noting that he is also an owner of xAI, a competitor to OpenAI, which complicates his position. Reducing OpenAI’s market presence would undoubtedly benefit xAI.
Other competitors also see an opportunity to curb OpenAI’s growth and influence in the AI industry. Meta has aligned with Musk, sending a letter to California Attorney General Rob Bonta and arguing that allowing the shift would have “seismic implications for Silicon Valley.” Meanwhile, Google has reportedly urged the US Federal Trade Commission to end OpenAI’s partnership with Microsoft, claiming the deal is “preventing them from competing in the burgeoning artificial intelligence market.”
No matter what happens with OpenAI’s restructuring plans, the impact on the tech industry and future startup founders will be profound.
OpenAI’s internal conflict between staying true to its ideals and navigating the realities of the modern business environment highlights that the romantic vision of a group of world-class researchers and engineers changing the world through a breakthrough invention alone is just that—a romantic vision. It demonstrates that achieving world-changing breakthroughs like AGI requires not only technological expertise but also substantial financial investments.
As one of the leading AI companies, OpenAI’s restructuring could set a precedent for how mission-driven organisations adapt to the demands of a competitive and capital-intensive market. It also raises important questions about how such transformative technologies should be governed and who should benefit from them.
If you enjoy this post, please click the 
button or share it.
Do you like my work? Consider becoming a paying subscriber to support it
For those who prefer to make a one-off donation, you can ‘buy me a coffee’ via Ko-fi. Every coffee bought is a generous support towards the work put into this newsletter.
Your support, in any form, is deeply appreciated and goes a long way in keeping this newsletter alive and thriving.
Eva’s First Steps Out of the Lab (6:25)
In this video, engineers and researchers from IHMC, a legendary name in robotics research and development space, share the first steps outside the lab of Eva, their robotic exoskeleton designed for people working in hazardous environments that require wearing heavy protective equipment. The walk outside the lab includes taking the first steps up and down stairs, as well as venturing outside the building, all accompanied by commentary from the person wearing the exoskeleton.
Predictions for Technology, Civilization & Our Future (38:08)
It’s that time of year when predictions for 2025 and beyond abound. Isaac Arthur envisions an optimistic near future, where advancements in AI and robotics enhance daily life, life extension technologies help us live healthier and longer, and humanity takes its first significant steps toward colonizing the solar system. These innovations could bring profound societal changes, new discoveries, and unparalleled opportunities. Arthur also explores the challenges of predicting the future, emphasizing the importance of adaptability, informed decision-making, and shaping the future through deliberate action.
Google CEO Pichai tells employees to gear up for big 2025: ‘The stakes are high’
The last two years have not been good for Google. The tech giant was caught off guard by the sudden rise of OpenAI and is now trying to regain its position as the leader in AI. Additionally, the company faces increased competition and regulatory hurdles. Amidst these challenges, Google CEO Sundar Pichai recently told employees that “the stakes are high” for 2025, emphasising the need for urgency and faster execution. Pichai also highlighted the importance of staying “scrappy,” citing Google’s early days as an example of innovation under constraints. The focus will be on leveraging advancements in AI (with Gemini playing a key role here) to address user problems and scale new technologies.
DeepSeek-V3, ultra-large open-source AI, outperforms Llama and Qwen on launch
Chinese AI startup DeepSeek released their new ultra-large model, DeepSeek-V3. According to the benchmarks provided by DeepSeek, this 671B parameters model is the strongest open model available and, in some benchmarks, outperforms GPT-4o and Claude 3.5 Sonnet.
Israel built an ‘AI factory’ for war. It unleashed it in Gaza.
The conflict in Gaza marks one of the first major uses of AI in warfare. The Israel Defense Forces (IDF) deploy advanced tools like “Habsora” and “Lavender” to analyze intelligence and suggest targets, significantly speeding up operations. While these tools enhance efficiency, internal audits and critiques have highlighted flaws such as language processing inaccuracies, over-reliance on algorithmic recommendations, and a lack of transparency in distinguishing between AI-derived and human-sourced intelligence. Critics argue this automation has lowered thresholds for collateral damage, raising civilian death tolls. The shift to AI-centric operations has also sparked debates within the IDF, with concerns about the erosion of traditional intelligence practices and compromised decision-making integrity. These challenges underline the ethical and operational dilemmas posed by the use of AI in modern warfare.
Tenstorrent and the State of AI Hardware Startups
Here is an excellent (and entertaining) analysis of Tenstorrent and why, according to
, Tenstorrent is one of the few AI hardware startups that makes sense. The piece explains in detail what Tenstorrent brings to the table and why they are probably the only AI hardware startup capable of breaking Nvidia’s and semi-custom (Google TPU, Amazon Trainium, Microsoft Maia) silicon moats. The post also contains a good analysis of the AI hardware startup ecosystem.
Performance of LLMs on Advent of code 2024
Over December, thousands of programmers were solving Advent of Code—an annual Christmas-themed series of coding challenges. Many used this as an opportunity to build their own coding agents and see how good they are at solving sometimes very challenging algorithmic problems. This post shares the results of one such experiment, which used GPT-4o, Gemini 1.5 Pro and Claude 3.5 Sonnet.
ChatGPT search vs. Google: A deep dive analysis of 62 queries
How does ChatGPT Search compare to Google Search? Here is a deep dive analysis comparing both search engines across 62 queries in various categories. The conclusion of this analysis is that Google Search remains the better solution for most searches, with ChatGPT Search being surprisingly competitive when it comes to informational queries.
If you’re enjoying the insights and perspectives shared in the Humanity Redefined newsletter, why not spread the word?
Nvidia’s next move: Powering humanoid robots
After conquering AI, Nvidia is focusing on the next big thing: robotics. Nvidia aims to be an OEM supplier, supporting the global community of robot makers rather than competing directly with manufacturers such as Tesla. The company took steps towards this goal in 2024 and it looks like to double down on this approach in 2025 with the launch of a new generation of compact computers for humanoid robots, called Jetson Thor, in the first half of the year.
Figure AI ships Figure 02 humanoid robots to a paying customer
Brett Adcock, the CEO of Figure AI, shared on LinkedIn that the robotics startup has become revenue-generating and has delivered its Figure 02 humanoid robots to an undisclosed commercial client. Figure AI emerged from stealth in January 2023 and has rapidly developed, iterated, and tested humanoid robots. In 2023, the company raised $70 million in Series A funding and later secured a $675 million Series B round in 2024, with OpenAI among its investors.
BYD officially enters humanoid robot race as global talent search kicks off
A new player is entering the already crowded humanoid robotics scene. BYD, a leading Chinese EV maker, is joining the field of humanoid robots. Aside from announcing a global recruitment programme to attract top talent, targeting master’s and doctoral graduates from 2024–2025, details about BYD’s humanoid robot remain sparse.
Saudi Arabia invests in robots to help build its Neom desert megacity
Saudi Arabia is currently in the midst of several ambitious construction projects, including the Line megacity and the twin skyscrapers Epicon. The recently secured bid to host the FIFA World Cup 2034 is only set to fuel the country’s construction boom further. To tackle the massive projects ahead, Saudi Arabia is turning to robotics to help speed up construction and has made a significant investment in Europe’s GMT Robotics through Neom’s strategic investment arm, the Neom Investment Fund (NIF).
The future of mRNA: companies and trials to watch in 2025
The Covid-19 vaccines have propelled mRNA vaccines into the spotlight. This article explores what can we expect from mRNA vaccines in 2025. Companies like Moderna and BioNTech are focusing on personalized cancer vaccines and HIV treatments, while Pfizer is leveraging its infrastructure for flu, shingles, and rare disease therapies. Other players, such as CureVac and Arcturus, are exploring second-generation mRNA technologies and novel delivery methods.
Genetically edited mosquitoes haven’t scaled yet. Why?
Mosquitoes are among the deadliest organisms, responsible for spreading diseases such as malaria, dengue fever, and the Zika virus. In this post,
explains the concept of gene drives—a method of genetically modifying mosquitoes to either suppress their populations or introduce anti-pathogenic genes, potentially eliminating their ability to transmit deadly diseases. While gene drives hold significant promise, the article provides an overview of their mechanisms and highlights the technical challenges (e.g., resistance development and species-specific variability), ecological risks, and ethical concerns tied to their deployment.
In 2025, People Will Try Living in This Underwater Habitat
Science fiction is full of underwater habitats where people live and work tens or hundreds of metres below the surface. British startup Deep is on a mission to make that futuristic vision a reality, with the first step being the launch of Vanguard, a rapidly deployable, expedition-style underwater habitat the size of a shipping container, capable of housing three people at depths of about 100 metres. Testing is scheduled to begin in the first quarter of 2025. The startup then plans to launch Sentinel, a permanent modular habitat system, in 2027. Deep hopes that its permanent underwater habitats will benefit marine science and drive advancements in marine engineering and advanced manufacturing techniques.
Thanks for reading. If you enjoyed this post, please click the button or share it.
Humanity Redefined sheds light on the bleeding edge of technology and how advancements in AI, robotics, and biotech can usher in abundance, expand humanity’s horizons, and redefine what it means to be human.
A big thank you to my paid subscribers, to my Patrons: whmr, Florian, dux, Eric, Preppikoma and Andrew, and to everyone who supports my work on Ko-Fi. Thank you for the support!
My DMs are open to all subscribers. Feel free to drop me a message, share feedback, or just say “hi!”
Si busca “CHATGPT” en su navegador, es probable que se tope en sitios web que parecen estar alimentados por OpenAI, pero no lo son. Uno de esos sitios, chat.chatbotapp.ai, ofrece acceso a “GPT-3.5” de forma gratuita y utiliza marca familiar.
Pero aquí está la cosa: no está dirigida por OpenAi. Y, francamente, ¿por qué usar un GPT-3.5 potencialmente falso cuando puedes usar GPT-4O de forma gratuita en el actual ¿Sitio de chatgpt?
Cuando el CEO de Google, Sundar Pichai, suba al escenario en la Conferencia de desarrolladores de Google I/O 2025 la próxima semana para entregar sus comentarios de apertura, espere que dos cartas dominen la discusión: la IA.
La inteligencia artificial se ocupa de gran parte del enfoque en Google en estos días, con características de IA que llegan a través de múltiples productos, proyectos centrados en la IA que capturan gran parte de la atención y predicciones del público sobre el futuro de la IA que asume muchos de los pronunciamientos públicos de la compañía.
Ya sea que se dé cuenta o no, la inteligencia artificial está en todas partes. Se encuentra detrás de los chatbots con los que hablas en línea, las listas de reproducción que transmites y los anuncios personalizados que aparecen en tu desplazamiento. Y ahora está tomando una personalidad más pública. Piense en Meta AI, que ahora está integrado en aplicaciones como Facebook, Messenger y WhatsApp; o Géminis de Google, trabajando en segundo plano en las plataformas de la compañía; o Apple Intelligence, lanzando a través de iPhones ahora.
AI tiene una larga historia, volviendo a una conferencia en Dartmouth en 1956 que primero discutió la inteligencia artificial como una cosa. Los hitos en el camino incluyen Eliza, esencialmente el primer chatbot, desarrollado en 1964 por el informático del MIT Joseph Weizenbaum y, saltando 40 años, cuando la función de autocompleta de Google apareció por primera vez en 2004.
Luego llegó 2022 y el ascenso de Chatgpt a la fama. Los desarrollos generativos de IA y los lanzamientos de productos se han acelerado rápidamente desde entonces, incluidos Google Bard (ahora Gemini), Microsoft Copilot, IBM Watsonx.ai y los modelos de LLAMA de código abierto de Meta.
Desglosemos qué es la IA generativa, cómo difiere de la inteligencia artificial “regular” y si la Generación AI puede estar a la altura de las expectativas.
En esencia, la IA generativa se refiere a sistemas de inteligencia artificial que están diseñados para producir un nuevo contenido basado en patrones y datos que han aprendido. En lugar de solo analizar números o predecir tendencias, estos sistemas generan salidas creativas como texto, música de imágenes, videos y código de software.
Algunas de las herramientas de IA generativas más populares en el mercado incluyen:
El principal entre sus habilidades, ChatGPT puede crear conversaciones o ensayos similares a los humanos basados en algunas indicaciones simples. Dall-E y MidJourney crean obras de arte detalladas a partir de una breve descripción, mientras que Adobe Firefly se centra en la edición y el diseño de imágenes.
No toda la IA es generativa. Si bien Gen AI se enfoca en crear contenido nuevo, la IA tradicional se destaca por analizar datos y hacer predicciones. Esto incluye tecnologías como el reconocimiento de imágenes y el texto predictivo. También se usa para soluciones novedosas en:
La IA que venció a los grandes campeones humanos en el ajedrez y el juego de mesa no fue una IA generativa.
Es posible que estos sistemas no sean tan llamativos como la Generación AI, pero la inteligencia artificial clásica es una gran parte de la tecnología en la que confiamos todos los días.
Detrás de la magia de la IA generativa hay modelos de idiomas grandes y técnicas avanzadas de aprendizaje automático. Estos sistemas están capacitados en grandes cantidades de datos, como bibliotecas completas de libros, millones de imágenes, años de música grabada y datos raspados de Internet.
Los desarrolladores de IA, desde gigantes tecnológicos hasta nuevas empresas, son conscientes de que la IA es tan buena como los datos que lo alimenta. Si se alimenta de datos de baja calidad, la IA puede producir resultados sesgados. Es algo con lo que incluso los jugadores más grandes en el campo, como Google, no han sido inmunes.
La IA aprende patrones, relaciones y estructuras dentro de estos datos durante el entrenamiento. Luego, cuando se le solicita, aplica ese conocimiento para generar algo nuevo. Por ejemplo, si le pide a una herramienta Gen AI que escriba un poema sobre el océano, no solo extrae versos preescritos de una base de datos. En cambio, está usando lo que aprendió sobre la poesía, los océanos y la estructura del lenguaje para crear una pieza completamente original.
Es impresionante, pero no es perfecto. A veces los resultados pueden sentirse un poco apagados. Tal vez la IA malinterpreta su solicitud, o se vuelve demasiado creativo de una manera que no esperaba. Puede proporcionar con confianza información completamente falsa, y depende de usted verificarla. Esas peculiaridades, a menudo llamadas alucinaciones, son parte de lo que hace que la IA generativa sea fascinante y frustrante.
Las capacidades generativas de IA están creciendo. Ahora puede comprender múltiples tipos de datos combinando tecnologías como el aprendizaje automático, el procesamiento del lenguaje natural y la visión por computadora. El resultado se llama IA multimodal que puede integrar alguna combinación de texto, imágenes, video y habla dentro de un solo marco, ofreciendo respuestas más contextualmente relevantes y precisas. El modo de voz avanzado de ChatGPT es un ejemplo, al igual que el proyecto Astra de Google.
No hay escasez de herramientas de IA generativas, cada una con su talento único. Estas herramientas han provocado la creatividad, pero también han planteado muchas preguntas además del sesgo y las alucinaciones, como, ¿quién posee los derechos del contenido generado por IA? O qué material es un juego justo o fuera de los límites para que las compañías de IA los usen para capacitar a sus modelos de idiomas; vea, por ejemplo, la demanda del New York Times contra Openai y Microsoft.
Otras preocupaciones, no son asuntos pequeños, implican privacidad, responsabilidad en la IA, los profundos profundos generados por IA y el desplazamiento laboral.
“Escribir, animación, fotografía, ilustración, diseño gráfico: las herramientas de IA ahora pueden manejar todo eso con una facilidad sorprendente. Pero eso no significa que estos roles desaparezcan. Simplemente puede significar que los creativos deberán mejorar y usar estas herramientas para amplificar su propio trabajo”, Fang Liu, profesor de la Universidad de Notre Dame Dame y Coeditor-Chief de las transacciones de ACM en las transacciones de Probabilista, contó el aprendizaje en el poderoso de la máquina probabilística, le dijo a Cetnet.
“También ofrece una forma para las personas que tal vez carecen de la habilidad, como alguien con una visión clara que no puede dibujar, pero que puede describirlo a través de un aviso. Así que no, no creo que interrumpa a la industria creativa. Con suerte, será una co-creación o un aumento, no un reemplazo”.
Otro problema es el impacto en el medio ambiente porque la capacitación de grandes modelos de IA utiliza mucha energía, lo que lleva a grandes huellas de carbono. El rápido ascenso de la Generación AI en los últimos años ha acelerado las preocupaciones sobre los riesgos de la IA en general. Los gobiernos están aumentando las regulaciones de IA para garantizar el desarrollo responsable y ético, especialmente la Ley de IA de la Unión Europea.
Muchas personas han interactuado con los chatbots en el servicio al cliente o han utilizado asistentes virtuales como Siri, Alexa y Google Assistant, que ahora están en la cúspide de convertirse en Gen AI Power Tools. Todo eso, junto con las aplicaciones para ChatGPT, Claude y otras herramientas nuevas, es poner ai en sus manos. Y la reacción pública a la IA generativa se ha mezclado. Muchos usuarios disfrutan de la conveniencia y la creatividad que ofrece, especialmente para cosas como escribir ayuda, creación de imágenes, soporte de tareas y productividad.
Mientras tanto, en la encuesta global de IA 2024 de McKinsey, el 65% de los encuestados dijo que sus organizaciones usan regularmente IA generativa, casi el doble de la cifra reportada solo 10 meses antes. Industrias como la atención médica y las finanzas están utilizando Gen AI para racionalizar las operaciones comerciales y automatizar tareas mundanas.
Como se mencionó, existen preocupaciones obvias sobre la ética, la transparencia, la pérdida de empleos y el potencial del mal uso de los datos personales. Esas son las principales críticas detrás de la resistencia a aceptar la IA generativa.
Y las personas que usan herramientas de IA generativas también encontrarán que los resultados aún no son lo suficientemente buenos para el tiempo. A pesar de los avances tecnológicos, la mayoría de las personas pueden reconocer si el contenido se ha creado utilizando Gen AI, ya sean artículos, imágenes o música.
AI ha secuestrado ciertas frases que siempre he usado, por lo que debo autocorrectar mi escritura a menudo porque puede parecer una IA. Muchos artículos escritos por AI contienen frases como “en la era de”, o todo es un “testimonio de” o un “tapiz de”. La IA carece de la emoción y la experiencia que viene, bueno, ser una vida humana y viviente. Como explicó un artista en Quora, “lo que AI hace no es lo mismo que el arte que evoluciona de un pensamiento en un cerebro humano” y “no se crea a partir de la pasión que se encuentra en un corazón humano”.
La IA generativa no es solo para técnicos o personas creativas. Una vez que obtienes la habilidad de darle indicaciones, tiene el potencial de hacer gran parte del trabajo preliminar por ti en una variedad de tareas diarias.
Digamos que está planeando un viaje. En lugar de desplazarse por páginas de resultados de búsqueda, le pide a un chatbot que planifique su itinerario. En cuestión de segundos, tiene un plan detallado adaptado a sus preferencias. (Ese es el ideal. Por favor, verifique siempre sus recomendaciones).
Un propietario de una pequeña empresa que necesita una campaña de marketing pero que no tiene un equipo de diseño puede usar una IA generativa para crear imágenes llamativas e incluso pedirle que sugiera copia publicitaria.
No ha habido un avance tecnológico que haya causado tal boom desde Internet y, más tarde, el iPhone. A pesar de sus desafíos, la IA generativa es innegablemente transformadora. Está haciendo que la creatividad sea más accesible, ayudando a las empresas a racionalizar los flujos de trabajo e incluso inspirar formas completamente nuevas de pensar y resolver problemas.
Pero quizás lo más emocionante es su potencial, y estamos rascando la superficie de lo que estas herramientas pueden hacer.
ChatGPT es probablemente el ejemplo más popular de IA generativa. Le das un aviso y puede generar texto e imágenes; Código de escritura; Responder preguntas; resumir el texto; borrador de correos electrónicos; y mucho más.
La IA generativa crea contenido nuevo como texto, imágenes o música, mientras que la IA tradicional analiza los datos, reconoce patrones o imágenes y hace predicciones (por ejemplo, en medicina, ciencia y finanzas).
Remove.bg: La Revolución en la Edición de Imágenes que Debes Conocer
Cómo Comenzar a Utilizar ChatGPT: Una Guía Completa para Principiantes
Startups de IA en EE.UU. que han recaudado más de $100M en 2024
Cómo Empezar con Popai.pro: Tu Espacio Personal de IA – Guía Completa, Instalación, Versiones y Precios
Deepgram: Revolucionando el Reconocimiento de Voz con IA
Perplexity aplicado al Marketing Digital y Estrategias SEO
Suno.com: La Revolución en la Creación Musical con Inteligencia Artificial
Dos periodistas octogenarios deman a ChatGPT por robar su trabajo
Inside the OpenAI-DeepSeek Distillation Saga & Alibaba’s Most Powerful AI Model Qwen2.5-Max
De ChatGPT a mil millones de agentes
