Can a YouTube video really fix your wet phone? | The Vergecast
27 Aug 2024 (20 days ago)
Intro in new studio
- The speaker is in a new studio, which has a YouTube play button.
- The speaker will be discussing upcoming VR and AR headsets from companies like Meta and Snap.
- The speaker will also be discussing a YouTube video that claims to remove water from phones.
The water-damaged phone incident
- A Samsung Galaxy s24 was dropped in a river and submerged for 10-15 minutes.
- The phone was retrieved and, although the screen was still on, a warning notification indicated water damage.
- Instead of drying out the phone, a YouTube video was played that emitted sounds intended to expel water from the phone's speakers.
Understanding how speakers work
- Conventional speakers, regardless of size, largely operate on the same principle using magnets and coils.
- Electrical currents passing through a coil within a magnetic field generate motion, pushing and pulling a piston-shaped component to move air and create sound.
- The frequency of the piston's movement dictates the tone, with lower frequencies corresponding to bass and higher frequencies to treble, while the amplitude of movement determines the volume.
Testing the water removal theory
- A theory was proposed that if Apple Watches have a water ejection feature utilizing sound, iPhones might too, but it's not included because iPhones have more potential points of ingress.
- An experiment was conducted where four phones - a Google Pixel 7 Pro, iPhone 13, Google Pixel 3, and Nokia 7.1 - were submerged in a UV dye solution to test water resistance and the effectiveness of water ejection videos.
- Results showed the Pixel 7 Pro had no liquid ingress, the iPhone 13 had some residue, the Pixel 3 had residue in multiple locations including under the screen, and the Nokia 7.1 had residue and corrosion, suggesting water ejection videos might help but aren't a guaranteed solution.
Gadget season and upcoming headsets
- It is currently “gadget season”, a time when tech companies typically release new products.
- Snap will release its fifth generation AR spectacles in September.
- Snap’s AR spectacles are not expected to be sold to the public and will function as a developer kit for its lens creators.
Snap's struggle in AR hardware
- Snap's CEO believes the company can compete in the AR hardware space, despite facing competition from Meta, which is investing billions of dollars in AR development.
- Snap aims to be a key player in the anticipated shift towards smart glasses and AR glasses, which are predicted to eventually replace smartphones.
- While the widespread adoption of AR technology was initially forecasted to happen sooner, it is now expected to occur towards the end of the decade, around 2028.
Meta's AR glasses Ambitions
- Meta is considered the most likely company to successfully bring AR glasses to the mainstream.
- Meta will be showcasing its AR glasses prototype, Project Orion, which has been in development since 2018 and has received significant investment.
- Project Orion is not expected to be released as a consumer product due to its high production cost and reliance on prototype technology.
Meta's focus on affordable AR
- Meta has prioritized affordability in its approach to AR development, as exemplified by its decision to discontinue a high-end project due to cost concerns.
- Meta's focus on price is seen as a potential drawback, as it may be hindering the development of more advanced and desirable AR products.
- Meta's AR strategy involves a multi-year roadmap that includes the release of smart glasses with small displays in the near future, followed by full-fledged consumer AR glasses in the later years of the decade.
AI first mover advantage (Vergecast Hotline)
- OpenAI, through ChatGPT's early success, gained significant brand recognition and market share, becoming synonymous with AI for many.
- While OpenAI initially held a technological edge, the AI field is rapidly evolving, with companies like Anthropic and Google making significant strides, eroding OpenAI's early lead.
- The increasing cost and complexity of developing large language models may limit the number of companies capable of competing in the AI market, potentially leading to market consolidation around a few key players.