Meta's press conference was a major fiasco. We talked to several Silicon Valley experts and discovered three overlooked truths.

At the just - concluded Meta Connect conference, what was supposed to be a highlight moment turned into a "live - broadcast accident" that made the global audience hold their breath.

Embarrassment occurred when the presenter put on the new Meta AI glasses and tried to demonstrate their powerful real - time AI Q&A function. Facing a not - so - complex instruction - "How to make Korean steak sauce", the AI assistant built into the glasses gave a vague answer and then got stuck in an infinite loop. No matter how many times the presenter asked "What's the next step", all that was exchanged were the AI's ignoring repetitions and silences. Eventually, the demonstration was forced to stop in complete silence.

For ordinary audiences, this might just be a laughing stock at the tech gala and a topic for after - dinner chats. However, for decision - makers in the capital market and industrial strategy, this scene epitomizes the core contradictions and dilemmas of the entire AI wearable market.

It raises a series of deeper and more crucial questions: Why, despite the capital's enthusiastic support and the tech giants' all - in approach, has the AI glasses, hailed as the "next - generation computing platform", failed to have its own "iPhone moment"? Is Meta's "stumble" an isolated technical accident or does it reveal the systematic bottlenecks that the entire industry faces in terms of technical paths, supply - chain maturity, and user - value definition?

In this long article, Silicon Rabbit will combine insights from its Silicon Valley expert team to penetrate the hype of the press conference and explore the real answers behind these questions with you.

01

Under the spotlight, Meta presented its latest offering in the field of AI glasses. On the surface, the "hardware score" of this offering seems quite good:

The camera has been upgraded from the barely - usable 12 - megapixel of the previous generation to the mainstream level capable of recording 3K videos;

The battery life has been significantly optimized. With the charging case, it can last up to 30 hours, basically eliminating users' "battery anxiety";

Not to mention the flagship model Meta Ray - Ban Display targeting the AR market, which finally brings the core function of "information display" into Meta's product line.

However, when looking beyond these parameter figures, what investors really need to examine is the strategic intention behind these upgrades.

Frankly speaking, this is more of a "linear optimization" rather than the "disruptive innovation" that the market has been eagerly awaiting. It addresses some obvious shortcomings of the previous models but fails to point out a brand - new path for the industry's future. The most crucial evidence lies in its core - the chip.

The new glasses still use the Qualcomm Snapdragon AR1 platform, which has been on the market for over a year and is commonly used in the industry. This means that its computing - power ceiling has already been set, unable to support more complex AI applications and revolutionary interactive experiences.

As for the seemingly avant - garde "neural wristband", it is more of an exploratory bet on future interaction forms rather than a mature solution.

It tries to bypass the limitations of voice and touch control, but the multiple malfunctions during the on - site demonstration expose the huge gap between this cutting - edge technology's stability and practicality. Whether users are willing to wear an additional accessory for the glasses remains an unknown that needs to be verified by the market.

Therefore, we can draw a preliminary conclusion: Meta's newly launched product is essentially an iterative product designed for "positioning". It shows the "helplessness" and "compromise" of the tech giant when facing the current technical bottlenecks - when a revolutionary breakthrough cannot be achieved, it arranges and optimizes existing technologies to maintain market enthusiasm and user attention.

This compromise reveals a deeper dilemma in the entire AI wearable market, which is far more worthy of our vigilance than the "fiasco" of a press conference.

02

Meta's "fiasco" is not an isolated case but a microcosm of the "big dreams, harsh reality" situation in the entire AI glasses market. Looking beyond the market hype, we will find that all players, whether from China or the US, are trapped by three structural "truths".

1. Who is paying for the "value - ambiguous" semi - finished products?

The blueprints painted by the capital market and industry reports are undoubtedly exciting. According to IDC's prediction, the global shipments of AR/VR devices are expected to maintain high - speed growth in the next few years. As the lightweight vanguard, AI glasses are highly anticipated. However, behind the impressive shipment data lies the "high return rate" that channel dealers are reluctant to mention.

The fundamental reason behind this is the "severe ambiguity of the value proposition of current AI glasses".

It tries to combine the functions of "headphones + camera + information assistant", but fails to provide an experience that surpasses mature devices in each individual function.

Its sound quality is no match for professional TWS headphones; its photo - taking quality is far from the computational photography ability of smartphones; and its so - called AI assistant, limited by network latency and model capabilities, is even less responsive and accurate than directly searching on a mobile phone.

After paying thousands of yuan, users get a compromised product that is "jack - of - all - trades, master of none". This "try - and - abandon" phenomenon clearly shows that the market needs a revolutionary product that can provide new and irreplaceable core value, not a simple combination of functions. Before that, most sales are just paying for the industry's "public beta".

2. The supply - chain shackles under the "impossible trinity"

All hardware startups have to make trade - offs, and in the field of AI glasses, this is reflected in the classic "impossible trinity" of weight, battery life, and computing power.

Greater computing power means a powerful chip to handle real - time AI tasks, but this inevitably leads to higher power consumption.

Longer battery life requires a larger - capacity battery to support the high - power - consumption chip, which directly increases the weight and volume of the glasses.

Lighter weight is a prerequisite for users to wear the glasses all day, but this restricts the battery capacity and heat - dissipation space, thus limiting the computing power.

Currently, all manufacturers are struggling to find a balance in this triangular dilemma, and the key to breaking the deadlock - the upstream supply chain - is not ready.

The core bottleneck lies in the chip. Whether it's Meta or domestic manufacturers, most of them use "general - purpose" solutions like the Qualcomm Snapdragon AR series. They are essentially variants of mobile - phone SoCs and are not designed for the extreme scenarios of AI glasses, which need to be "on all day with ultra - low power consumption".

The entire industry is waiting for a dedicated chip like the "S series" that Apple developed for the Apple Watch. It needs to have an extremely high energy - efficiency ratio and be able to handle complex AI tasks with milliwatt - level power consumption. Without this "heart", AI glasses will always be stuck in the embarrassing situation of being "power - bank accessories".

3. Chinese and US players are "in the same boat", with similar core technology stacks

Many people habitually think that Meta's technological strength will "crush" domestic manufacturers. However, at least in the field of AI glasses, this is not the case. If we disassemble the current mainstream products on the market, we will find that their technology stacks are surprisingly similar, presenting a situation of "being in the same boat".

Core computing power: The homogenized chip solutions determine similar computing - power ceilings.

Optical display: Whether it's the Birdbath or waveguide solutions, there are only a few global suppliers of core optical modules. The bottlenecks in cost, yield, and display effect are common.

Software ecosystem: All players are in the very early stage of building a "killer app". Although Meta has a social platform, it is still exploring how to perfectly integrate it with the form of glasses. Domestic manufacturers are trying to combine with high - frequency scenarios such as navigation and office work but have not found the breakthrough point either.

Therefore, the current market competition is more of a "micro - innovation" competition in terms of industrial design, product definition, and cost control based on a similar "arsenal" rather than a crushing competition due to technological gaps.

This just shows that the entire market is still on the eve of a technological breakthrough. The real moat has not been formed yet, and everyone is on the same starting line, waiting for the "starting gun" from the upstream supply chain.

03

Meta's "fiasco" and the industry's bottlenecks may mean disappointment for ordinary consumers, but for savvy investors, this is the starting point for value discovery.

When the market is dominated by public information and short - term emotions, the real opportunities are hidden in the in - depth questions that cannot be answered from press releases and financial reports.

When making decisions, we must ask the following questions that go beyond the surface:

Regarding the business model: When all manufacturers are struggling in the hardware quagmire, what exactly will be the "killer app" for AI glasses? Will it be a new super C - end app, or will the real moat first appear in vertical B - end fields such as healthcare, industry, and logistics, forming a number of "small but beautiful" high - profit markets?

Regarding the industry's end - game: Apple has shown extraordinary strategic patience with the Vision Pro. What exactly is its internal definition of the end - game of "spatial computing"? How will it be deeply integrated with Apple's own large - scale AI model strategy to build a "spatial operating system" ecosystem that outsiders cannot penetrate? What does this mean for the current Android - camp AI glasses manufacturers in the long - term competitive landscape?

Regarding technological barriers: As we all know, Qualcomm's current AR - series chips are essentially "optimized versions" of mobile - phone chips, and the contradiction between power consumption and computing power is still prominent. Then, what real - time rendering and low - latency problems that general - purpose chips cannot solve does a real "AR - native AI chip" need to address at the underlying architecture? Will the next technological breakthrough be advanced packaging (such as Chiplet) or a new computing architecture?

These questions point to the core value segments of the industrial chain and also point to investment opportunities worth billions or even hundreds of billions.

However, relying solely on public reports is far from enough to answer them. The real investment alpha comes from the first - hand experiences and in - depth thinking of core figures in the front - line of the industry, which are not easily accessible. It could be an informal exchange or a closed - door technical discussion.

This in - depth insight from the front - line can instantly cut through the market noise and provide clear guidance for investment decisions.

This article is from the WeChat official account "Silicon Rabbit" (ID: gh_1faae33d0655), author: Silicon Rabbit. Republished by 36Kr with permission.