TikTok Shop, the social commerce marketplace of TikTok, is introducing a new section dedicated to secondhand luxury items in the United Kingdom. This move positions TikTok Shop in direct rivalry with existing platforms such as The RealReal, Vestiaire Collective, Depop, Poshmark, and Mercari. The offering has been present at TikTok Shop U.S. for a duration exceeding six months.

The addition of this new category enables clients in the United Kingdom to conveniently buy second-hand luxury garments, designer purses, and various accessories from within the TikTok application. Upon its inception, the platform offers a selection of only five British brands, namely Sellier, Luxe Collective, Sign of the Times, HardlyEverWornIt, and Break Archive.

Since its introduction in 2022, TikTok Shop has generated sales of approximately $1 billion or more in merchandise value. Nevertheless, despite its triumph, some contend that TikTok Shop is undermining the short-form video-sharing platform, alleging that counterfeit and substandard merchandise are inundating the market. The purchase of pre-owned luxury goods online carries the greatest danger of encountering counterfeit products, even for major e-commerce platforms such as Amazon, eBay, and others, which also struggle with ensuring authenticity.

TikTok Shop, like other resale marketplaces, implements an anti-counterfeit policy that ensures a complete reimbursement in the event that a seller is verified to have sold a counterfeit item. Bloomberg has disclosed that the corporation is engaged in discussions with luxury goods company LVMH to enhance efforts to combat counterfeiting.

Every secondhand brand on TikTok Shop in the U.S. must possess certificates from third-party authenticators. TikTok collaborated with authentication providers Entrupy and Real Authentication to verify the authenticity of designer handbags available on the platform.

Concurrently, a representative from TikTok informed me that the five British brands each possess their own internal verification procedure. They declined to provide the commencement date for accepting secondhand brands other than their own.

TikTok Shop’s introduction of a used luxury category is a calculated maneuver to access the expanding market for previously owned high-end goods. The secondhand luxury market is a prosperous industry valued at around $49.3 billion (€45 billion) in 2023, with global sales of pre-owned designer items.

Moreover, this expansion is in line with the growing inclination of individuals towards adopting preloved fashion, and it creates new opportunities for secondhand brands in the U.K. to access a broader client demographic. The prevalence of secondhand fashion on TikTok is apparent, as seen by more than 144,000 TikTok postings utilizing the hashtag #secondhandfashion, resulting in nearly 1.2 billion views.

Today’s statement follows closely after the U.S. House of Representatives passed a bill mandating that ByteDance sell TikTok or else risk a ban in the U.S. This bill seems to be gaining favor in the Senate. An embargo would have a significant impact on American merchants who sell their products on the application. As per the company’s statement, the brief video-sharing application produced a total of $14.7 billion in revenue for small- to mid-size enterprises in the year 2023.

Airchat is a recently developed social media application that promotes and encourages users to engage in open and spontaneous conversations.

Last year, a previous iteration of Airchat was released. However, yesterday the team, which included Naval Ravikant, the founder of AngelList, and Brian Norgard, a former product executive for Tinder, rebuilt the application and reintroduced it on both iOS and Android platforms. At present, Airchat is exclusively accessible via invitation. However, it has already achieved a ranking of #27 in the social networking category on Apple’s App Store.

Airchat has a user interface that is visually familiar and easy to understand. Users can follow other users, navigate through a feed of posts, and interact with those posts by replying, liking, and sharing them. The distinction comes from the fact that the content consists of audio recordings for both posts and replies, which are subsequently converted into written form by the application.

Airchat automatically starts sending messages, which you can quickly navigate through by vertically swiping up and down. If you have the desire, you have the option to pause the audio and only read the text. Additionally, users have the capability to exchange photographs and videos. However, it appears that audio is the main point of interest for everyone, and Ravikant explains that it has the potential to significantly change the way social apps function, especially when contrasted to text-based platforms.

Upon my recent enrollment in Airchat, the majority of the messages I encountered pertained to the application itself. Notably, Ravikant and Norgard actively engaged in responding to inquiries and seeking input from users.

“All humans are inherently capable of harmonious interactions with one another; it simply necessitates the use of our innate communication abilities,” Ravikant stated. “The prevalence of online text-only media has created the false belief that people are unable to get along, when in reality, everyone is capable of getting along.”

Past instances have seen digital entrepreneurs placing their bets on speech as the upcoming significant trend in social media. However, Airchat’s utilization of asynchronous, threaded messages provides a distinct experience compared to the transient live chat rooms that briefly gained popularity on Clubhouse and Twitter Spaces. Norgard claimed that this method eliminates the obstacle of stage fright when it comes to participation, as individuals have the freedom to make multiple attempts at producing a message without anybody being aware.

Indeed, he stated that during discussions with the first users, the team discovered that the majority of individuals currently utilizing AirChat exhibit introverted and timid characteristics.

Personally, I have not yet persuaded myself to publish anything. I was primarily intrigued by observing how other individuals were utilizing the application. Additionally, I had a complex emotional connection with the auditory perception of my own speech.

However, there is value in listening to Ravikant and Norgard articulate their perspective instead of solely relying on written transcriptions, as the latter may overlook subtle aspects such as excitement and tone. I am particularly interested in observing how deadpan humor and shitposting are conveyed, or not, in audio format.

I also encountered some difficulty with the velocity. The application automatically sets the audio playing to double the normal speed, which I found to be artificial, especially considering that the main purpose is to promote human interaction. To reset the speed, simply press and hold the pause button. However, when the speed is set to 1x, I observed that I would begin to skim through longer postings while listening, and I would often jump forward before listening to the entire audio. However, perhaps that is acceptable.

However, Ravikant’s conviction in the efficacy of speech to reduce hostility does not always obviate the requirement for content-filtering functionalities. According to him, the feed operates based on intricate regulations that aim to conceal spam, trolls, and those that either you or they may prefer not to receive messages from. However, at the time of publication, he had not yet replied to a subsequent user inquiry regarding content moderation.

When questioned about monetization, namely the introduction of advertisements, whether in audio format or otherwise, Ravikant stated that the company is currently not under any obligation to generate revenue. (He characterized himself as “not the exclusive investor” but rather as a significant stakeholder in the company.)

“Monetization is of little importance to me,” he stated. “We will operate this project with minimal financial resources if necessary.”

30,000 individuals gathered in Las Vegas this week to receive the most up-to-date and innovative information from Google Cloud. The only thing they heard was continuous generative AI. Google Cloud primarily operates as a vendor that provides cloud infrastructure and platform services. Without prior knowledge, it is possible that you overlooked this information amidst the abundance of AI news.

While acknowledging the impressive showcase by Google, it is worth noting that, similar to Salesforce’s event in New York City last year, the company did not focus much on its primary operations, save when discussing generative AI.

Google unveiled a range of artificial intelligence (AI) improvements aimed at assisting users in leveraging the Gemini large language model (LLM) and enhancing productivity throughout the platform. Undoubtedly, it is a commendable objective. During the primary keynote on Day 1 and the subsequent Developer Keynote, Google incorporated a substantial number of demonstrations to exemplify the capabilities of these solutions.

However, several of them were overly basic, especially considering the constraint of being condensed into a keynote presentation with a restricted time frame. Their reliance was primarily on cases within the Google ecosystem, despite the fact that most companies store a significant portion of their data in repositories that are not affiliated with Google.

Several of the examples seemed feasible without the use of artificial intelligence. During an e-commerce demonstration, the presenter contacted the vendor to finalize an online transaction. The purpose of its design was to demonstrate the communication capabilities of a sales bot. However, in reality, the customer could have completed the task on the website with ease.

Generative AI possesses powerful applications, such as code generation, content analysis with query capabilities, and log data analysis to determine the cause of a website outage. In addition, the company has produced task- and role-based agents that may effectively utilize generative AI to assist individual developers, creative individuals, employees, and others.

However, when it comes to developing AI tools using Google’s models, rather than using the ones created by Google and other vendors for their customers, I couldn’t help but notice that they were downplaying many of the challenges that could hinder the successful implementation of generative AI. Despite attempts to downplay the difficulty, the truth is that integrating advanced technology into large businesses poses a significant obstacle.

Significant transformation is not simple
Similar to earlier technological advancements over the previous 15 years, such as mobile, cloud, containerization, and marketing automation, there have been numerous claims of potential benefits. However, each of these developments brings up its own degree of intricacy, and prominent corporations proceed with more prudence than we could envision. Artificial intelligence (AI) appears to require significantly more effort and resources than what Google or other major vendors are openly acknowledging.

Our experience with past technological revolutions has shown that they often generate excessive excitement and ultimately result in widespread disappointment. After several years, we continue to observe prominent corporations that, while having the opportunity, are only experimenting with or completely abstaining from utilizing these sophisticated technologies, even long after their introduction.

Companies may fail to take advantage of technological innovation due to various factors. These include organizational inertia, a rigid technology infrastructure that hinders the adoption of newer solutions, and a group of individuals within the company who oppose any well-intentioned initiatives. These individuals may belong to legal, HR, IT, or other departments and may reject substantive change for reasons such as internal politics.

Vineet Jain, the Chief Executive Officer (CEO) of Egnyte, a company specializing in storage, governance, and security, identifies two categories of companies: those that have already made a substantial transition to the cloud and will find it relatively easier to adopt generative AI, and those that have been slow in embracing new technologies and are likely to face challenges in adopting generative AI.

He engages in conversations with numerous firms that predominantly rely on on-premises technology and have a significant amount of progress to make before considering the potential benefits of AI. “We engage with numerous ‘late’ cloud adopters who have either not initiated or are in the initial stages of their pursuit of digital transformation,” Jain informed.

The introduction of AI may compel these organizations to carefully consider pursuing digital transformation, although they may encounter difficulties due to their significant lag in progress, according to his statement. “Before incorporating AI, these companies must first address and resolve the existing issues and establish a robust data security and governance framework,” he stated.

The data was consistently the main factor
Major industry players such as Google present the implementation of these solutions as straightforward, but the apparent simplicity on the surface does not guarantee that it is not complex behind the scenes. Throughout this week, I frequently encountered the notion that the quality of the data used to train Gemini and other extensive language models is crucial. It is evident that if the input data is of poor quality, the output generated by generative AI will also be of poor quality.

The process begins with the collection and analysis of data. If your data is not organized, it will be challenging to prepare it for training the LLMs for your specific use case. Kashif Rahamatullah, a principal at Deloitte responsible for overseeing the Google Cloud practice, expressed his admiration for Google’s recent developments. However, he also highlighted that certain firms without organized data may encounter difficulties when using generative AI solutions. “The initial AI conversation often transitions into a focus on data cleaning and consolidation, as this is crucial for maximizing the benefits of generative AI,” Rahamatullah explained.

Google has developed generative AI tools to facilitate data engineers in constructing data pipelines that connect to both internal and external data sources within the Google ecosystem. “The purpose is to enhance the efficiency of data engineering teams by automating the labor-intensive tasks associated with data movement and preparation for these models,” explained Gerrit Kazmaier, Google’s Vice President and General Manager for Database, Data Analytics, and Looker, in an interview with.

This will be beneficial for data integration and data cleansing, particularly in firms that have made significant progress in their digital transformation. However, for firms like the ones mentioned by Jain, who have not made significant progress in terms of digital transformation, these tools developed by Google could pose further challenges.

Furthermore, it is important to note that AI presents additional hurdles beyond mere implementation. According to Andy Thurai, an analyst at Constellation Research, this is true whether one is developing an application based on an existing model or attempting to create a customized model. “During the implementation of either solution, companies must consider governance, liability, security, privacy, ethical and responsible use, and compliance with these implementations,” stated Thurai. And all of that is significant.

Executives, IT professionals, developers, and other attendees of GCN this week may have sought insights into Google Cloud’s future offerings. However, if they were not actively seeking AI or if they were not adequately prepared as an organization, they may have left Sin City feeling overwhelmed by Google’s intense focus on AI. Organizations that lack digital expertise may need a significant amount of time before they can fully utilize these technologies, especially those that are not as comprehensive as the solutions provided by Google and other suppliers.