A new post was published on OpenAI CEO Sam Altman’s blog that spoke about the company’s ideas of making the benefits of AI widely distributed for all.
He shared more on the matter including how a computed budget was amongst the many other strange-sounding ideas that he was ready to put forth. The goal was to make the masses benefit from the approach.
The historical impact of this technological progress hints that most of the metrics that users worry about are getting better with time. Altman mentioned that the balance between matters like capital and labor could get messy and it might need early intervention.
Solutions to such issues including Altman’s concept for compute budget (i.e. bringing AI to the masses) might appear easier said than done. Today, AI is affecting the labor market and giving rise to serious job cuts and downsizing in several departments. Experts issued a warning that mass unemployment is a potential outcome relating to the rise of AI when not supported by the correct government policies.
This isn’t the first time, Altman shared how AGI is also very near which can solve even the most complex issues out there today. No matter what, AGI ceases to be perfect and will never compare to human potential. Altman says this could require serious human supervision as well as direction.
All AGI systems won’t have the best ideas and while it can do some good things, it will be bad at so many others. The real value related to AGI will arise from running systems on a big scale. Similar to the thinking of Anthropic’s CEO, Altman sees thousands of those capable of tackling tasks in different fields of work.
It’s definitely not a cheap vision but Altman says that a person can spend huge sums of money and get the right gains in return with AI. This is why OpenAI is ready to start talks to raise $40B in funding. They’ve pledged to spend $500B with the help of partners on the huge data network.
Altman also speaks about cases where the costs for AI fall up to ten times every year. In other words, while pushing AI boundaries won’t make it cheaper, more users are going to get access to capable systems along the way.
So many inexpensive AI models keep popping up as we speak. This includes DeepSeek and more that support this cause. There’s similar evidence that suggests both training and development costs fall to a new low. Both Altman and Amodei argued that there are massive investments at stake here that need to attain the AGI level of AI and more.
In terms of how the company hopes to roll out these AGI systems, Altman refused to get into the minute details. He said that some major decisions will soon be coming and there’s a lot to consider about the safety of this project.
Let’s not forget how OpenAI is in the midst of converting into a corporate structure that’s far from traditional. It will reach $100B in revenue by 2029 which is equal to what was seen for Target and Nestle’s yearly sales.
Image: DIW-AIgen
Read next: UC Berkeley Researcher Criticizes Billion-Dollar AGI Race, Says AI Can’t Know Everything
He shared more on the matter including how a computed budget was amongst the many other strange-sounding ideas that he was ready to put forth. The goal was to make the masses benefit from the approach.
The historical impact of this technological progress hints that most of the metrics that users worry about are getting better with time. Altman mentioned that the balance between matters like capital and labor could get messy and it might need early intervention.
Solutions to such issues including Altman’s concept for compute budget (i.e. bringing AI to the masses) might appear easier said than done. Today, AI is affecting the labor market and giving rise to serious job cuts and downsizing in several departments. Experts issued a warning that mass unemployment is a potential outcome relating to the rise of AI when not supported by the correct government policies.
This isn’t the first time, Altman shared how AGI is also very near which can solve even the most complex issues out there today. No matter what, AGI ceases to be perfect and will never compare to human potential. Altman says this could require serious human supervision as well as direction.
All AGI systems won’t have the best ideas and while it can do some good things, it will be bad at so many others. The real value related to AGI will arise from running systems on a big scale. Similar to the thinking of Anthropic’s CEO, Altman sees thousands of those capable of tackling tasks in different fields of work.
It’s definitely not a cheap vision but Altman says that a person can spend huge sums of money and get the right gains in return with AI. This is why OpenAI is ready to start talks to raise $40B in funding. They’ve pledged to spend $500B with the help of partners on the huge data network.
Altman also speaks about cases where the costs for AI fall up to ten times every year. In other words, while pushing AI boundaries won’t make it cheaper, more users are going to get access to capable systems along the way.
So many inexpensive AI models keep popping up as we speak. This includes DeepSeek and more that support this cause. There’s similar evidence that suggests both training and development costs fall to a new low. Both Altman and Amodei argued that there are massive investments at stake here that need to attain the AGI level of AI and more.
In terms of how the company hopes to roll out these AGI systems, Altman refused to get into the minute details. He said that some major decisions will soon be coming and there’s a lot to consider about the safety of this project.
Let’s not forget how OpenAI is in the midst of converting into a corporate structure that’s far from traditional. It will reach $100B in revenue by 2029 which is equal to what was seen for Target and Nestle’s yearly sales.
Read next: UC Berkeley Researcher Criticizes Billion-Dollar AGI Race, Says AI Can’t Know Everything
