Tech
TikTok sale puts app’s algorithm in the spotlight
President Donald Trump announced on Sept. 19, 2025, a preliminary agreement for the sale of a majority stake in TikTok from Chinese tech giant ByteDance to a group of U.S. investors following Trump’s negotiation with Chinese leader Xi Jinping.
The deal would create a new U.S.-only version of the app, bringing it into compliance with a law signed by former President Joe Biden on April 23, 2024, and upheld by the Supreme Court on Jan. 17, 2025. Specifics of the deal remain to be hammered out, and left unresolved is the fate of the video sharing app’s core algorithm—and what that means for TikTok’s millions of U.S. users.
The Chinese government has indicated it will not permit ByteDance to sell the algorithm, because it is classified as a controlled technology export, per Chinese law. Meanwhile, U.S. tech industry executives and some lawmakers say compliance with the law requires the algorithm to be under American control. The deal as proposed includes licensing the algorithm so that it remains Chinese intellectual property while the U.S. version of the app continues to use the technology.
TikTok’s For You Page algorithm is widely considered the most important part of the app. As one analyst put it: “Buying TikTok without the algorithm would be like buying a Ferrari without the engine.”
The algorithm’s value lies in its uncanny capacity to anticipate users’ content preferences. Many users claim it knows them better than they know themselves—a sentiment that has evolved into a curious mix of spiritual belief and conspiracy theorizing, as my colleagues and I have documented. Other scholars have similarly noted that users feel more intimately seen and known by TikTok’s algorithm than those powering other popular platforms.
I have studied social media algorithms for nearly a decade, exploring how our relationships with them have evolved as they become increasingly entwined with daily life. As both a social media scholar and TikTok devotee, I want to shed some light on how the algorithm works and how the app might change in the wake of its sale.
How the TikTok algorithm works
In some ways, the TikTok algorithm does not differ significantly from other social media algorithms. At their core, algorithms are merely a series of steps used to accomplish a specific goal. They perform mathematical computations to optimize output in service of that goal.
There are two layers to the TikTok algorithm. First, there is the abstract layer that defines the outcome developers wish to accomplish. An internal document shared with The New York Times specified that TikTok’s algorithm optimizes for four goals: “user value,” “long-term user value,” “creator value” and “platform value.”
But how do you turn these goals into math? What does an abstract concept like “user value” even mean? It’s not practical to ask users whether they value their experience every time they visit the site. Instead, TikTok relies on proxy signals that translate abstract outcomes into quantifiable measures—specifically, likes, comments, shares, follows, time spent on a given video and other user behavior data. These signals then become part of an equation to predict two key concrete outcomes: “retention,” or the likelihood that a user will return to the site, and “time spent” on the app.
The TikTok For You Page algorithm relies on machine learning for predicting retention and time spent. Machine learning is a computational process in which an algorithm learns patterns in a dataset, with little or no human guidance, to produce the best equation to predict an outcome. Through learning patterns, the algorithm determines how much individual data signals matter for coming up with a precise prediction.
A Wall Street Journal investigation found that the amount of time users spend watching each video plays a large role in how the algorithm chooses videos it suggests to users. Using the equation it has generated to predict retention and time spent, the algorithm assigns a score to each video and ranks possible videos that could be shown to the user by this score. The higher the score for an individual user, the more likely the video will appear in their feed.
Of course, content characteristics and other users additionally inform recommendations, and there are other subprocesses folded into the equation. This step is where algorithmic moderation usually comes in. If a video looks like engagement bait or has excessive gore, for example, the content’s score will be penalized.
What’s likely to change for US users
The sale has not been finalized, and what happens to the algorithm is unresolved. However, it’s fairly certain that TikTok will change. I see two key reasons for change.
First, the proposed app’s U.S.-only user population will alter the makeup of the underlying dataset informing algorithmic recommendations on an ongoing basis. As the kinds of content and users come to reflect American cultural preferences, values and behaviors, the algorithm may be slightly different as it “learns” new patterns.
Moreover, not all users will choose to join the new app, especially if it is seen as under the control of Trump’s allies. The current deal reportedly would give an 80% share to U.S. investors, including 50% to new investors Oracle, Silver Lake and Andreessen Horowitz. These investors’ have connections to Trump, and an apparent provision of the deal allows the U.S. government to select one board member. This may result in a user population—and data—reflective of a narrower realm of interests and ideologies.
Second, it’s possible that the majority share owners of the new app will decide to adjust the algorithm, particularly when it comes to content moderation. The new owners may wish to modify TikTok’s Community Guidelines according to their view of acceptable and unacceptable speech.
For example, TikTok’s current Community Guidelines prohibit misinformation and work with independent fact-checkers to assess the accuracy of content. While Meta used to follow a similar approach for Instagram and Facebook, in January 2025 it announced that it would end Meta’s relationships with independent fact-checkers and loosen content restrictions. YouTube has similarly relaxed its content moderation this year.
The bottom line is algorithms are highly sensitive to context. They reflect the interest, values and worldviews of the people who build them, the preferences and behaviors of people whose data informs their models and the legal and economic contexts they operate within.
This means that while it’s difficult to predict exactly what a U.S.-only TikTok will be like, it’s safe to assume it will not be a perfect mirror image of the current app.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Citation:
TikTok sale puts app’s algorithm in the spotlight (2025, September 22)
retrieved 22 September 2025
from https://techxplore.com/news/2025-09-tiktok-sale-app-algorithm-spotlight.html
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.
Tech
Top 1Password Coupons for November 2025
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Save With Vitamix Promo Codes and Deals This Month
I’ve been hooked on smoothies in an almost superstitious way ever since college: A fruit smoothie is like a good luck charm, promising the health you feel you deserve despite all your other bad decisions. But in my more recent adult life, a good blender is the passport to taqueria salsas, Oaxacan-style mole, and all the delicate emulsions I once had to buy at restaurants and in jars.
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Vitamix New Ascent X5 With Stainless Steel Container
Vitmix’s top-of-the-line blender model, Ascent X5, is now constructed with a stainless steel container. The 48-ounce stainless steel container is not only huge and hygienic, the machine itself combines an intuitive touch interface with a refined, timeless design. The non-reactive stainless steel material resists stains, odors, and corrosion, and expertly handles hot, cold, and acidic ingredients. This futuristic gadget also has an automatic self-cleaning program and ten blending programs for popular items like smoothies, soups, frozen cocktails and more for a precise blend, every time.
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Does Vitamix Offer Free Shipping?
Glad you asked. Vitamix is offering free standard shipping for orders above $99. This pretty much means that ground shipping is free for blenders at the current discounts. Priority shipping is not free, however.
The WIRED Gear Team’s Favorite Vitamix Blenders
WIRED has long been singing the praises of the classic Vitamix 5200. The model made a blender convert out of contributing reviewer Joe Ray after he realized that the “model of preference for blender aficionados around the world” was also his key to home mole and Oaxacan-style cookery.
A similar road-to-Damascus moment beset WIRED contributing reviewer Heather Arndt Anderson when she tested the Vitamix Ascent X2, also currently on a $50 promo discount. “The more I thought about it,” she wrote, “the more I realized that maybe I’ve never been a blender person because I never had a good blender.” Anderson also made a big batch of mole and avoided passing out from chile fumes, then moved on to homemade masa and a Georgian walnut spread. She regretted only that the blender wasn’t easier to clean.
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Additional Vitamix Deals and Sales in 2025
Vitamix tends to offer a number of other deals and sales throughout the year, like Presidents Day, but the next one won’t crop up till Mother’s Day. Other deals to expect crop up during the summer, alongside the eternal Black Friday and Cyber Monday Deals.
Tech
Research drives commercialization of energy-efficient solar cell technology toward 40% efficiency milestone
Third-generation solar cell technology is advancing rapidly. An engineering research team at The Hong Kong Polytechnic University (PolyU) has achieved a breakthrough in the field of perovskite/silicon tandem solar cells (TSCs), focusing on addressing challenges that include improving efficiency, stability and scalability.
The team has conducted a comprehensive analysis of TSC performance and provided strategic recommendations, which aim to raise the energy conversion efficiency of this new type of solar cell from the current maximum of approximately 34% to about 40%.
The team hopes to accelerate the commercialization of perovskite/silicon TSCs through industry-academia-research collaboration, while aligning with the nation’s strategic plan of carbon peaking and neutrality and promoting the development of innovative technologies such as artificial intelligence through renewable energy.
The research team comprises leading scholars including Prof. Li Gang, Chair Professor of Energy Conversion Technology and Sir Sze-yuen Chung Endowed Professor in Renewable Energy, and Prof. Yang Guang, Assistant Professor, both of the PolyU Department of Electrical and Electronic Engineering.
They conducted a critical review of the challenges and future prospects of perovskite/silicon TSCs titled “Towards efficient, scalable and stable perovskite/silicon tandem solar cells,” which has been published in the journal Nature Photonics.
Tackling stability and manufacturing challenges
“While lab-scale devices have shown impressive efficiency advancement, further efforts are needed to improve their reliability, including minimizing efficiency losses from small-area devices to large-area modules,” said Prof. Gang. “Special focus should also be given to ensuring that the manufacturability of materials and methods aligns with industrial standards.”
To address these issues, Prof. Guang and the team highlighted several critical technical challenges. First, the intrinsic instability of perovskite materials under environmental stresses such as moisture, oxygen, ultraviolet light and thermal fluctuations remains a major challenge. Second, translating tandem devices to commercial-scale modules requires overcoming hurdles related to uniformity, defect control and large-area fabrication.
Although preliminary outdoor testing of perovskite/silicon TSCs has been conducted, certified data on their long-term reliability remain scarce. To better assess the actual lifetime and commercial potential of these cells, the researchers recommend rigorous accelerated stability testing based on standardized procedures outlined by the International Electrotechnical Commission.
Additionally, while perovskite raw materials are relatively low-cost, the use of rare elements and heavy metal lead in most cell designs raises significant environmental and regulatory concerns. The research therefore advocates for the development of sustainable alternatives, along with efficient recycling or lead sequestration strategies to enable viable commercialization.
Promoting industry-academia-research collaboration
The PolyU team advocates for industry-academia-research collaboration through a multidisciplinary approach that integrates material science, device engineering and economic modeling to advance this promising photovoltaic technology. “The development of efficient and reliable perovskite/silicon TSCs must address these remaining scientific challenges to achieve lower levelized electricity costs,” said Prof. Guang.
“The team hopes this research will facilitate the transition of the technology from laboratory studies to commercial fabrication, while closely aligning with the nation’s strategic plan of carbon peaking and neutrality. By providing a stable supply of high-efficiency renewable energy, we aim to deliver green and reliable power support for high-energy-consuming industries such as artificial intelligence, thereby helping to achieve a low-carbon transformation of the energy structure.”
More information:
Guang Yang et al, Towards efficient, scalable and stable perovskite/silicon tandem solar cells, Nature Photonics (2025). DOI: 10.1038/s41566-025-01732-y
Citation:
Research drives commercialization of energy-efficient solar cell technology toward 40% efficiency milestone (2025, November 10)
retrieved 10 November 2025
from https://techxplore.com/news/2025-11-commercialization-energy-efficient-solar-cell.html
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.
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