Загрузка видео...

Не удалось загрузить видео

На главную

What happens to competitive advantage when every company has access to the same AI tools? Just as two businesses with similar people and resources can produce very different results, companies will differ in how effectively they put AI to use. That still requires human judgment, instinct, and intuition about...

18,385 просмотров • 5 дней назад •via X (Twitter)

Комментарии: 2

Фото профиля Jamal Thompson
Jamal Thompson5 дней назад

I still find working out what to ask it the hardest bit.

Фото профиля Dragonbyte🐉❤️🦁🍀
Dragonbyte🐉❤️🦁🍀5 дней назад

When every firm can access similar tools, differentiation shifts to the questions teams ask and the feedback they keep. AI advantage compounds when attention becomes a repeatable practice, not just a new capability.

Похожие видео

Chamath Palihapitiya believes AGI may already exist inside leading AI labs and the bigger story is that advanced intelligence is becoming cheaper and more widely available (Save this). Chamath Palihapitiya argues that the public may be focused too much on benchmark rankings, while frontier labs are already developing models capable of complex reasoning, coding, research, and tool use. The main question is how quickly companies will release these systems and how much access they will provide. AGI has not been officially confirmed and strong benchmark results do not necessarily prove that a model can perform every intellectual task like a human. However, AI capabilities are improving quickly, while the cost of running advanced models continues to fall. That combination is important because cheaper AI can be used by more businesses for customer service, software development, research, marketing, financial analysis, and automation. Competition is also accelerating among OpenAI, Anthropic, Google, xAI, Meta, and open source developers because as more companies release capable models, users gain more choices and prices continue to decline. This creates a powerful cycle in which better models attract more users, more usage generates more revenue and data, and lower prices encourage companies to apply AI to additional tasks. The biggest challenge is moving from impressive demonstrations to measurable business results. Companies still need to redesign workflows, train employees, protect sensitive information, and prove that AI spending is producing a real return on investment. AI agents could create the next major increase in demand because they can plan tasks, use tools, check their work, retry failed actions and operate for long periods without constant human supervision. Even if each AI task becomes cheaper, total usage could grow much faster as businesses use models across more departments and this could increase demand for GPUs, high bandwidth memory, networking equipment, electricity, cooling systems, and data centers.

Milk Road AI

13,501 просмотров • 1 месяц назад