The First Major News in the AI Community for the Second Half of the Year: Meta Releases LLaMA 2, Fully Open Source and Free for Commercial Use.
In the AI Mid-Year Summary article shared last month, I mentioned that Meta had already achieved a significant leadership position in the AI open-source community with LLaMA. Now, Meta is leveraging its success and making a major move by launching LLaMA 2 today (July 19th) to further solidify its position.
Compared to the first generation of LLaMA, LLaMA 2 uses 2 trillion tokens (which represents the amount of text) for training and offers an input length of 4,096 tokens, which is twice the length of the previous generation.
Recently, the AI research community has been engaging in a competition regarding text length, focusing on the number of tokens that language models can process at once. This aims to enhance the language model's ability to demonstrate comprehensive contextual reasoning, leading to better AI performance.
OpenAI's ChatGPT, Anthropic's Claude, and some recently published research claim to have extended token lengths to 32,768, 100,000, and 1 million, respectively. While LLaMA 2 may seem shorter in comparison, it is crucial to note that LLaMA 2 is the only one among them that is open source.
In the announcement of LLaMA 2, Meta mentioned that its capabilities are still not as advanced as GPT-4. However, this precisely highlights a major challenge for OpenAI: In the future, every enterprise will need its own AI brain as an operational center, but this AI brain doesn't necessarily have to be as powerful or expensive as GPT-4.
What enterprises need is a customized AI model that can address their specific business challenges and "possess domain expertise". They don't require an all-knowing AI.
Since the first half of the year, with the initiation of the AI arms race centered around "downsizing the AI brain" (as mentioned in my previous article), the entire trend has been accelerating. LLaMA 2 has reached a new milestone as it is not only fully open source but also signifies a significant partnership announced by Meta.
Qualcomm and Meta have collaborated to integrate LLaMA 2 into smartphone chips, which will become a reality in 2024. This indicates that Meta has gained a first-mover advantage in the AI edge computing market. Currently, other big tech companies do not have a comparable open-source model to compete with LLaMA 2.
Let's not forget that in the past, Google achieved market dominance in the mobile operating system (OS) market by leveraging the open-source software Android. Meta missed the opportunity for mobile development and had to rely on the ecosystems of Apple and Google, constantly making adjustments due to privacy concerns and its advertising business models, as the ongoing competition among these three enterprises has never subsided.
This year, Zuckerberg decisively shifted Meta's focus from the metaverse to fully embrace AI. With (the accidental leak of) the first-generation LLaMA, Meta has opened up a new competitive landscape with the opportunity to explore deeper into everyone's smartphones.
Let's not forget what we have always emphasized: in the digital business domain, it's all about an ecosystem battle. Meta integrates three crucial weapons: AI chips, open-source AI models, and its existing powerful network effects. Amidst the clash between the two giants, Google and OpenAI/Microsoft, Meta has suddenly entered a new AI battlefield, aiming to start from community network applications and vertically delve into everyone's smartphone computing chips.
At this point, it has been proven that what I mentioned before: anyone claiming that Meta is absent or falling behind in the entire AI war is completely misjudging the situation.
Meta is not playing catch-up; instead, it has entered the AI battle from a completely different competitive angle. Many still have doubts about Zuckerberg's metaverse, but he is genuinely impressive. I have always advocated that AI's development will accelerate the growth of the metaverse. Looking back in a few years, we will realize that Zuckerberg was just taking a temporary detour.
According to rumors, Meta is conducting internal tests to deploy LLM (Large Language Model) on Messenger at a large scale. As the world's largest messaging platform, there is no better place for creating a large number of popular digital humans than Meta's portfolio. I'm quite certain that Meta will swiftly enter this market.
Therefore, the emerging generative AI companies, such as digital human companies, have been under the pressure lately. After all, once the tech giants catch up and assert their dominance, these companies could be heavily impacted.
The network effect remains the most advantageous moat controlled by big tech, and the second half of the year will be their home field. Startups relying solely on generative AI technology for entrepreneurship will face immense competitive pressure without a clear moat.
With the groundbreaking release of LLaMA 2, the industry has witnessed a bloom of open-source models being utilized to build various AI applications. Companies that have cautiously guarded their "exclusive large language models" as trade secrets and primary competitive advantages must swiftly construct an entire AI ecosystem and become new gateways to the internet. Otherwise, they risk being overshadowed and potentially consumed by the existing ecosystem of big tech companies.
Building a new ecosystem is not simple, and these enterprises will face a critical moment of survival in the second half of the year. The rapid pace of market change is truly remarkable.
