AkhenOsiris
$META
SCMP:
In an interview on the Chinese video channel Silicon Valley 101 broadcast on Wednesday, Tian Yuandong– previously research scientist director at Meta FAIR, the Facebook parent’s legacy Fundamental AI Research team – said limited computing resources had triggered internal conflicts inside the group, as large language models (LLMs) became a major focus of AI development around the world.
Tian’s assessment appeared to substantiate why Meta – which also owns Instagram, WhatsApp, Messenger and Threads – let go of around 600 employees from its AI research unit, months after the company revamped its strategy through the acquisition of data-annotation firm Scale AI and a poaching spree from rival AI laboratories. Meta confirmed the lay-offs, which included Tian, last month.
On the broadcast, Tian also cast a pessimistic view on the AI industry’s traditional scaling laws, which attributed improved AI system performance to increasing the size of a model’s parameters, training tokens and computational resources. “What we truly need to pursue is figuring out which kinds of models can move forward more efficiently and effectively,” he said. “Compute isn’t everything. We need a deeper understanding of how models work.”
While acknowledging that LLMs provided “an interesting path” for developing AI further, Tian questioned whether these systems were “the right one”. He pointed out that AI models were now trained on token volumes that far exceeded what was available to humans. He added that LLMs still lacked the ability of human beings to obtain data and dig deeper into it. “Perhaps our current training algorithms are not optimal,” he said. Tian also said open-source models would continue to thrive. AI systems are likely to become more specialised, focused on vertical domains and application-driven goals, rather than a universal model that is capable in every field, he added.
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$META
SCMP:
In an interview on the Chinese video channel Silicon Valley 101 broadcast on Wednesday, Tian Yuandong– previously research scientist director at Meta FAIR, the Facebook parent’s legacy Fundamental AI Research team – said limited computing resources had triggered internal conflicts inside the group, as large language models (LLMs) became a major focus of AI development around the world.
Tian’s assessment appeared to substantiate why Meta – which also owns Instagram, WhatsApp, Messenger and Threads – let go of around 600 employees from its AI research unit, months after the company revamped its strategy through the acquisition of data-annotation firm Scale AI and a poaching spree from rival AI laboratories. Meta confirmed the lay-offs, which included Tian, last month.
On the broadcast, Tian also cast a pessimistic view on the AI industry’s traditional scaling laws, which attributed improved AI system performance to increasing the size of a model’s parameters, training tokens and computational resources. “What we truly need to pursue is figuring out which kinds of models can move forward more efficiently and effectively,” he said. “Compute isn’t everything. We need a deeper understanding of how models work.”
While acknowledging that LLMs provided “an interesting path” for developing AI further, Tian questioned whether these systems were “the right one”. He pointed out that AI models were now trained on token volumes that far exceeded what was available to humans. He added that LLMs still lacked the ability of human beings to obtain data and dig deeper into it. “Perhaps our current training algorithms are not optimal,” he said. Tian also said open-source models would continue to thrive. AI systems are likely to become more specialised, focused on vertical domains and application-driven goals, rather than a universal model that is capable in every field, he added.
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