You can build your own basic educational LLM in under 2,000 lines of code.
This includes code for:
Data Curation, Neural Network, Training, Evaluation and Inference.
Data Collection & Quality are the hardest and most time-consuming part for most real-world AI projects.
-PyTorch is open‑source Machine Learning framework developed primarily by Meta AI ~ 2017.
-Transformer is a neural net architecture paper published by Google researchers in 2017.
These 2 have become key for nearly all major AI models, yet back in 2017 few could have imagined it
The key challenge in effectively harnessing AI capabilities is the difficulty of clearly articulating and conveying your ideas to the system. Some companies are already working to address this issue.
We should take these statements seriously, as the person making them has significant credibility also hr has insights into the technology that we don’t have. He isn’t trying to promote any of his products here.
We should take these statements seriously, as the person making them has significant credibility also hr has insights into the technology that we don’t have. He isn’t trying to promote any of his products here.
In developing world where healthcare is expensive or non existent people can get some healthcare support by allowing patients to seek initial advice or prescriptions from AI systems for non-critical medical conditions.(Governments should consider this)
In developing world where healthcare is expensive or non existent people can get some healthcare support by allowing patients to seek initial advice or prescriptions from AI systems for non-critical medical conditions.(Governments should consider this)
At present, no proven model exists for compensating people in a world where human labor is no longer essential. This is why, despite talk of UBI or UHI, most citizens remain unconvinced the challenge lies not in technology, but in politics and the distribution of economic power.
So far, most humanoid robots haven’t shown any capability other then dancing, running, or folding laundry which may grab headlines, but they’re still far from being economically viable tasks. It will be interesting to see impact of NVIDIA’s latest Jetson AGX Thor.
No one truly knows how powerful the next version of AI tools will be, hype aside. Yet with every release so far, AI’s capabilities have consistently exceeded expectations and surprised us all.
While humans typically specialize in one domain, AI now match and in some cases surpass human-level performance across many fields. This suggests that AGI is not far, when AI will surpass all human in all domains.
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