AI has come a long way, with each new model raising the bar on what’s possible—more power, more intelligence, more ability to understand and even mimic human thought. But now, OpenAI, one of the field’s front-runners, is facing something new: progress is slowing down. Their upcoming model, Orion, isn’t expected to deliver the same jaw-dropping improvements we’ve seen in the past. Instead, it’s likely to be a smaller, more measured step forward.
Reports from early testers suggest that while Orion does show improvements, it doesn’t have the same wow factor that took us from GPT-3 to GPT-4. And in some areas, like coding, it might not be noticeably better than what’s already available. This suggests a shift—not necessarily an end to progress, but maybe a different pace, one less about massive breakthroughs and more about incremental gains.
OpenAI seems to be adapting. They’ve created a new foundations team whose job is to find ways to push AI forward, even with limits on new data to train these models. One of their big ideas is to use synthetic data—data generated by other AI models—instead of relying exclusively on vast new troves of human-created content. This approach, along with some focused fine-tuning after the main training phase, might be the key to keeping AI progress on track.
It’s a practical move, especially when the traditional playbook—more data, bigger models, faster machines—isn’t delivering the same gains it once did. For years, AI has ridden a wave of ever-expanding resources, but with limits in sight, the industry is making a choice: pursue meaningful improvements, even if they aren’t earth-shattering, rather than chasing flashy leaps that may no longer be possible.
In many ways, this is a moment for AI to mature. Instead of relentless ambition for power, it’s about focusing on real-world impact, designing systems that are practical, ethical, and well-suited to their roles. It’s a new kind of progress—one that, perhaps, better matches the needs of the industries and people these technologies are meant to serve. And maybe, in a world so often fixated on speed, a little patience and recalibration is exactly what’s needed.
Read next: Study Reveals LinkedIn Videos Generate Five Times More Engagement Than Text Posts, Personal Flair Boosts Reach
Reports from early testers suggest that while Orion does show improvements, it doesn’t have the same wow factor that took us from GPT-3 to GPT-4. And in some areas, like coding, it might not be noticeably better than what’s already available. This suggests a shift—not necessarily an end to progress, but maybe a different pace, one less about massive breakthroughs and more about incremental gains.
OpenAI seems to be adapting. They’ve created a new foundations team whose job is to find ways to push AI forward, even with limits on new data to train these models. One of their big ideas is to use synthetic data—data generated by other AI models—instead of relying exclusively on vast new troves of human-created content. This approach, along with some focused fine-tuning after the main training phase, might be the key to keeping AI progress on track.
It’s a practical move, especially when the traditional playbook—more data, bigger models, faster machines—isn’t delivering the same gains it once did. For years, AI has ridden a wave of ever-expanding resources, but with limits in sight, the industry is making a choice: pursue meaningful improvements, even if they aren’t earth-shattering, rather than chasing flashy leaps that may no longer be possible.
- Also read: ChatGPT In The Spotlight: Popular AI Tool Transforms Into Revenue Powerhouse During October 2024
In many ways, this is a moment for AI to mature. Instead of relentless ambition for power, it’s about focusing on real-world impact, designing systems that are practical, ethical, and well-suited to their roles. It’s a new kind of progress—one that, perhaps, better matches the needs of the industries and people these technologies are meant to serve. And maybe, in a world so often fixated on speed, a little patience and recalibration is exactly what’s needed.
Read next: Study Reveals LinkedIn Videos Generate Five Times More Engagement Than Text Posts, Personal Flair Boosts Reach
