Zuckerberg paid a dividend of 700 million dollars, Meta's stock price rose 16%, and the open source plan was completed?
Reported by the Heart of the Machine
Heart of the Machine Editorial Department
Meta is coming out of the shadows.
With Meta's share price rising nearly 14% in after-hours trading on Thursday to a record high, the company announced its first-ever dividend payout.
According to the latest earnings call, Meta reported full-year 2023 revenue of $134.9 billion, an increase of 16% from 2022, and net profit of $39.1 billion, an increase of 69% year-on-year. Fourth-quarter revenue of $40.1 billion beat expectations of $39.18 billion and increased 25% year-over-year.
Beginning in March, Meta will pay a quarterly cash dividend of 50 cents to Class A and Class B common stock.
CEO Mark Zuckerberg, who owns about 350 million shares (13% of Meta's shares), will receive about $175 million in pre-tax income from quarterly dividends, or about $700 million over the course of a year, according to data compiled by Bloomberg.
"We had a great quarter as our community and business continued to grow. 」
While the company experienced a trough in market capitalization in 2022, Meta stock is up 168% over the past 12 months. The company's market capitalization has returned to the trillion-dollar ranks, and Zuckerberg's net worth has reached $142 billion.
Unlike the founders of some other big tech companies, Zuckerberg, the CEO, has never handed over power to anyone else and has been making long-term bets on trends such as the metaverse and artificial intelligence.
Meta has been on the same page in the AI space over the past few days: its generative AI large language model Llama can compete with OpenAI and Google's models, and Meta is also looking to integrate AI tools into its core products and is rumored to be using its own chips to power its AI systems. In a recent video, Zuckerberg hinted at Meta's grand plans to develop artificial general intelligence (AGI).
In addition to the better-than-expected results, the news also seems to have boosted confidence in Meta. It seems that Meta is coming out of the gloom.
With Llama, Meta is breaking new groundgrounds in the AI space
If you go back to more than a year ago, perhaps no one would have thought that Meta, which was once mired in the quagmire of the metaverse, would be able to regain a game with a set of open-source models, and even reopen a battlefield outside the closed-source world of AI dominated by OpenAI and Google.
This battleground is based on Meta's open-source Llama family of models, and its members are extremely active. Many of the large AI models that have been fine-tuned on top of it claim to have surpassed GPT-3.5 or even approached GPT-4 (such as the recently leaked "Miqu" model from Mistral, which is close to GPT-4 performance and is an early version of Mistral's Llama 2-based training for its own customers).
At the same time, the influence of Meta's open-source model in the industry is gradually emerging. Many large international companies, such as Wells Fargo and IBM, are now deploying open source models based on Llama 2.
Meta responded to why it chose the open source route on its recent earnings call. Meta admits that they have indeed gained a lot from the road of open source, including the improvement of the basic model and the transition from the model to the product. And, they argue, there are several strategic advantages to the leaders of member open source:
First, open-source software is generally more secure and reliable, while operating more efficiently due to continuous feedback, review, and development from the community. This is a big issue because security is one of the most important issues in artificial intelligence. The increased efficiency and reduced computational costs have also benefited everyone, including Meta.
Second, open-source software often becomes the industry standard. Meta says Meta can easily incorporate other companies' innovations into its own products when other companies standardize on Meta's technology stack. It's subtle, but the ability to learn and improve quickly is a huge advantage, and being the industry standard makes this practice possible.
Finally, open source is very popular among developers and researchers, which helps Meta recruit the best talent.
However, it may take some time for these effects to be fully felt, as Meta's open-source model series was released later than ChatGPT.
In a video released last month, Zuckerberg said that they are training Llama 3 at full strength and will stick to the open source route in the future. To train the model, they will buy 350,000 NVIDIA H100 GPUs, and self-developed chips are also on the agenda.
For computing power, Meta is also building cores
According to Reuters, Meta is working on a custom chip "Artemis" for data centers.
This is a positive turn for Meta's internal AI chip project, which follows Meta's executives who decided to stop investing in self-developed chips during the company's financial crunch in 2022.
But last year, Meta first announced its self-developed first-generation training and inference accelerator, MTIA. Artemis is the second generation of Meta's in-house chip production line, helping to reduce Meta's reliance on NVIDIA chips while controlling the costs associated with running generative AI workloads.
Dylan Patel, founder of research firm SemiAnalysis, said that with Meta's scale of operations, the successful deployment of its own chips has the potential to save hundreds of millions of dollars in energy costs and billions of dollars in chip procurement costs every year.
The chips, infrastructure and energy needed to run AI applications have become a huge depression for tech companies' investments, partially offsetting the gains surrounding this wave of technology.
A Meta spokesperson confirmed plans to start production of the updated chip in 2024 and said it would work in tandem with the hundreds of thousands of off-the-shelf GPUs the company is purchasing.
"We believe that our in-house developed accelerators are highly complementary to GPUs on the market and can deliver the best combination of performance and efficiency for Meta-specific workloads," the spokesperson said in a statement. 」
As you may remember, Xiaozha recently released a short video saying that the company plans to purchase about 350,000 flagship H100 processors from Nvidia by the end of 2024, and with other suppliers, Meta will have a total of 600,000 H100 computing power.
Over the past few years, the rise of generative AI has been fueled in part by Nvidia's advanced GPUs. In turn, the H100 has become highly sought after and extremely expensive due to short supply, putting Nvidia on the list of trillion-dollar market capitalization companies for the first time.
This dynamic has also prompted tech giants such as Microsoft, Meta, OpenAI, Amazon, and Google to start developing their own AI processors. At the same time, chipmakers such as Nvidia, AMD, and Intel are also caught in an arms race to release newer, more efficient, and more powerful chips.
As the demand for generative AI services continues to grow, it's clear that chips will be the next big focus for tech companies.
With the rapid development of open-source AI models, coupled with active actions in computing power and other aspects, Meta's image in the tech circle is being reshaped. Of course, in the competition in 2024, Meta will also face a more severe test. Are you bullish on this company?
Reference Links:
https://www.reuters.com/technology/meta-deploy-in-house-custom-chips-this-year-power-ai-drive-memo-2024-02-01/
https://www.businessinsider.com/metas-profits-first-ever-dividend-2024-2
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