While VR devices languish, AR glasses seem to have become the focus of those looking to capitalize on a “VR Lite” world that can provide additional visual functionality without the massive headgear that keeps VR out of the mainstream.  That said, even lower on the VR/AR scale are the latest category of ‘glasses’, AI glasses.  AI glasses are just what they seem to be, relatively standard glasses with the ability to connect to an AI system that can be used for a number of functions.  They tend to be inexpensive relative to AR and VR devices, with functionality varying with each new device.
The category is ruled by Meta’s (FB) Ray-Ban glasses that were released in October 2023.  They have sold over 2 million units since and are the standard against which competitors are marked or mark themselves.  Yet, when CE brands see unit volumes in the millions it is hard to resist sticking a bunch of engineers into a facility somewhere and seeing what they come up with in a few months.  While Meta basks in the glory of being the best by far in a ‘new’ category, the competition is beginning to come from other substantial players, with China’s Xiaomi (1810.HK) the latest to release its own branded AI glasses.  We note that while AI glasses are a standalone category today, we expect the category to merge with AR glasses at some point in the near future as consumers will see AI glasses as the ‘low-end’ of the visual headset spectrum, with AR being the mid-tier and VR being the upper tier.
Given the success of the Meta Ray-Ban’s Xiaomi did not stray far from both the Ray-Ban look and functionality, and we already get the feel that while AI glasses are reasonably inexpensive, it’s going to be a knock-down, drag-out battle on price once the basics are established.  Just like the smartphone world, where a new feature or application can sustain a line for a year or two,  AI glasses and eventually AR glasses will be one and the same, although at a lower price point, and for AI glasses that become available under $300 (currently) and eventually under $200, it is easy to see how volumes can become attractive to CE brands that deal in millions of units regularly.

As can be seen in the images above, there is very little physical difference between the Xiaomi Ai glasses and the Meta Ray-bans, and when it gets down to components that similarity remains.  Here is a comparison of the feature sets of both.  These are for the basic models of each.

So, what can these glasses do, considering they are only a bit more expensive than the average pair of glasses at a discount retailer (avg. ~$184).?

• Translation - They have the ability to translate conversation in real time, with the number of languages available dependent on the model or brand.  The Xiaomi glasses include 10 languages including Chinese.
• Text recognition – AIs have made text recognition a much easier task then having to run documents through a physical OCR or digital documents through software to break down image-based text into actual editable text.  AI systems can do this easily using the camera that is built-in.
• Object Recognition – Object recognition requires either a massive database and a matching system, or a model that has been trained on large amounts of image and video data.  Again, using the camera, one can have the AI examine an object that the user is looking at and classify or describe it.  Taking it further, in theory, the user can then ask the AI about the object, such as where it might be sold and in what colors.
• Voice commands and Assistants – Multiple microphones allow voice commands to be used to initiate processes or systems, such as video recording.  This allows the user to initiate the command without having a free hand.
• QR Codes – The glasses can scan mobile QR codes for payments , avoiding having to take out your phone to scan QRs.
• Transcription – The glasses are able to record meetings, conferences, and  conversations and create transcripts and translations.
• Video and Image Capture – Using the embedded camera, the user can capture images and video (30 fps), take video calls, or livestream.
• Audio – The glasses have a 5 microphone array that can be used for voice calls and built-in open-ear speakers in the frames so no earbuds are necessary.
• Integration – This is where things can get a bit more difficult as applications need to be able to interact with the OS and, potentially, applications on a smartphone.  , so things like livestreaming might be limited to only those live streaming applications that have APIs or other necessary interfaces to work with the glass’s hardware.  This is where proprietary systems can cause AI glasses users to become frustrated and be unable to use all of the features.  However, as glasses become more popular the interface issue should fade as both applications and hardware modules become more standardized.

One question that comes to mind at this relatively early product stage is whether the direction will be whether brands will take the route of maintaining a price range in the $200- $400 range and compete by adding features or will the direction be to keep hardware costs low and keep reducing the price to attract more users?  We expect the former.

​The EU has been on Apple’s (AAPL) case concerning its rules for developers on the App Store since early 2019 when Spotify (SPOT) filed a formal complaint with the commission, followed by a formal investigation commencing 15 months later.  The heart of the Spotify complaint was the fact that it was forced to charge higher prices for its upper tier subscriptions through the Apple App Store because of the 30% commission charged to developers.  It could steer users to its website for in-app purchases, but that alternative was made difficult by Apple rules.  The EU fined Apple €1.8 billion in March of last year for what it called abusive practices concerning music streamers, primarily in response to the anti-steering rules Apple had in place for years.
The DMA (Digital Markets Act), finalized last year, provides legislation in the EU that protects against these kinds of practices, and Apple is continuing to modify its App Store rules in order to comply with DMA and not incur additional fines.  Most recently they made a number of changes relating to the App Store that they hope will convince the EU Commission that they are not creating unfair trading conditions, reducing competition, or ultimately limiting consumer choices and causing higher prices.
Here are the key changes Apple has made to its EU APP Store Policies:
Store Service Fee – This replaces the flat commission model that Apple had previously used if developers used an external payment link within their apps.
              Tier 1 – 5% - This tier comes with App Review, Content moderation, Privacy labels, Trust & Safety features, and basic app delivery.  It does not include auto App updates, ratings & reviews, Downloads across devices, natural language search, Apple Store featuring & marketing, app tabs, and advanced app insights & performance metrics, essentially cutting away many of the App Store’s promotional tools.
              Tier 2 – 13% - Includes all App Store features including those omitted in Tier 1.  Small businesses (earning less than $1m) and those apps with auto-renew can lower the fee to 10%.  Tier 2 is the default, but developers can opt to Tier 1 once per quarter for each app on each storefront.
Initial Acquisition Fee – This 2% fee applies to sales of digital products made by new users who are ‘acquired’ through the App Store and then make an external purchase.  This 2% fee continues (on monthly subscriptions or items) for the first 6 months of the new user’s timeline.  Small business developers can waive this fee.
Core Technology Commission – 5% - This is a new commission that replaces the previous and highly controversial CTF that was charged when a user made an external purchase through an App Store application.  As of now, the previous CTF (Core Technology Fee) is still in effect but is being phased out (Target 1/1/2026) and the CTC phased in.  The old CTF was a €0.50 fee charged to the developer for each install after the first install over 1 million each year.  The big complaints about this fee came from developers who provided their apps for free, having no sales offset to the fee for popular apps.
Other than fees, Apple has made a few other changes to assuage the forces in the EU, such as allowing developers to promote their applications and goods on external websites (other than their own) and alternative marketplaces, and has reduced the number of times the “You are leaving the App Store…” warning appears when users click on an external payment link in an app.  Apple still has not implemented a choice of payment options for individual apps (either App Store in-app or ‘alternative’ payment options) but seems to be heading in that direction, albeit less than voluntarily.
The developer community seems mixed about Apple’s new EU system, some continue to criticize Apple for maintaining a structure that is anti-competitive while others see the new tiered structure more flexible, but the bottom-line comes from the EU commission who must determine whether the new rules meet DMA standards.  If not Apple could face another round of massive fines for even small violations.  

Earlier this week Japan Display (6740,JP) converted the MOU it had signed with its largest shareholder Ichigo Trust (2337.JP) into an official agreement, much of which will be executed next month.  The deal, which is comprised of:

• New warrant issuance (3.852 billion underlying shares for ¥95.6 billion or $662.5m US)
• The transfer of certain IP from JDI to Ichigo (LCD & OLED)
• The sales of the JDI Mobara fab to Ichigo and partial leaseback
• The repayment of ¥65b in loans from Ichigo from the Mobara sale proceeds.
• Ichigo’s surrender of previous warrants at zero value

Assuming that the warrants are exercised (¥25 exercise price – Current Price ¥20), Ichigo’s ownership will increase from 78.2% to 91.6%.  The exercise period extends from 7/15/25 to 11/30/28.  The proceeds from the warrant sales will be allocated (approximately):

• 45% for working capital through 2028
• 25% for Display, Sensor & Advanced Packaging Capex
• 10% for R&D and technology commercialization
• 5% to build out JDI IP
• 5% for strategic partnerships
• 5% for digital improvements (ERP, etc)

There is little that can be said at this point as JDI has made numerous attempts to ‘fix’ the problems that have been besetting the company for the last 10 years.  Way back in 2016 it was rumored that Apple (AAPL) was considering converting at least some of the LCD iPhone displays that were supplied to it by JDI and others to OLED.  While that did not happen until late in 2017, Japan Display management took the head-in-the-sand approach, assuming OLED was just a fad, which ultimately proved incorrect.  Since then JDI has made a number of attempts to find a new technology path but has been unable to find anything that might become an offset to its currently almost non-existent display business.  The company does have some potential photolithographic OLED material deposition IP but has been unable to find a partner to scale the process.
Current management has certainly taken steps to reduce costs and tail off money-losing businesses, but building traction for new processes or products is both time-consuming and expensive, and given the turmoil that is the everyday meat and potatoes of the CE space, this most recent financing might be enough to carry the company through the next 2 ½ years.  That said, it is just a band-aid unless JDI can get one of its new ideas, concepts, processes, or products to stick, a task even the big boys and girls are having trouble with currently.

On June 16, Trump siblings Eric and Don Jr. announced Trump Mobile (pvt) and its flagship phone the T1.  The date was a commemoration of the 10th anniversary of the 2016 announcement of Donald Trump’s 2016 presidential bid.  The mobile service, an MVNO (Mobile Virtual Network Operator) that operates on the network infrastructure of existing major carriers, also promised roadside assistance and telehealth services along with carriage.  The Trump Mobile website initially claimed that the T1 would be “built in the US” and a follow-up release by the Trump Organization indicated that the phone was “proudly designed and built in the United States”, while other early promotional material declared that the phone was “proudly made right here in the USA”, and the original product description stated, “The T1 Phone isn’t just powerful—it’s brought to life right here in the USA. With American hands behind every device, we bring care, precision, and trusted quality to every detail”, along with a website banner that said, “Made in USA”.
On or around June 22, the Trump Mobile website was subject to a number of language changes.  The “Made in USA” banner was removed, “built in the U.S.” was changed to “brought to life right here in the USA”, “proudly designed and built in the United States” was changed to “Proudly American”, and “proudly made right here in the USA” was changed to “American Proud Design”.  While the “Made in the USA” banner was removed and not replaced the statement “designed with American values in mind” appeared.  The specifications for the T1 itself also seemed to have changed, as the OLED display, originally noted to be 6.78”, is now 6.25” and the 12GB of RAM originally stated in the phone specs is no longer on the site.  No processor was named in the original promo, which is unusual, and no processor has been named in the updated promo. 
One other significant change that was made was the date of availability, which was originally stated to be in September and now states “later this year”, but as we originally noted, this was not a Trump Organization product, just one that was licensed by the TO, and with the intense scrutiny and iffy detail, there is considerable speculation that the phone might be undergoing a slight ‘design change’ to better fit with the updated and likely more accurate advertising.  The Trump organization has made it clear that it is in no way responsible for the development and manufacturing of the network or the device, but when you pull apart the partnerships, operating companies, Delaware corporations and LLCs behind the product, the responsible party is as expected.  Frozen Steaks anyone?

While we track memory prices, we don’t often comment on spot prices unless they are doing something unusual and for the last few weeks DRAM prices have been heating up, with this week seeing the greatest w/w gain of the year in most DRAM categories.  This has pushed DDR4 prices above DDR5 prices, typically something that does not often happen in the daily course of events.  DDR4 supply is tight but much of the panic is coming from the lack of a definitive trade agreement details with China that might settle potential semiconductor and memory trade issues.  The steep part of the increase has been in a relatively short timeframe but should it extend it will add to the cost pressure CE companies are feeling before they start worrying about tariff issues…

There are dozens of cases in the US courts decrying the fact that AI companies have used copyrighted material to train LLMs under the ‘Fair Use’ doctrine.  Authors, artists, musicians, and content creators look at this type of use, much of which is done without copyright permission, as stealing the material that they created and have the legal right to capitalize on, should they so desire.  Given that there is considerable case law on fair use, one might expect rulings to be relatively simple, but that is certainly not the case as the use cases here are ones that are relatively new to the courts and do not follow many of the case formats that have governed fair use in other instances.
A recent ruling by a US California District judge in favor of Anthropic AI (pvt), the developer of the ‘Claude’ LLM models, could change the way in which models are trained, leaning more to the ‘fair use’ side of Section 107 of the US Copyright Act.  In order to understand the basics of the decision, here are a few facts about Section 107:

• The section discusses the limited use of copyrighted material without explicit permission under certain circumstances, trying to balance the exclusive rights of copyright owners with the public interest in free expression, creativity, and information availability. 
• These are not clear cut rules with easily followed formulas and as they are fact specific, they need to be evaluated on a case-by-case basis. 
• On a more general basis there are some instances where copyrighted material ‘May’ be considered ‘fair use’, meaning no permission needs to be granted, but each instance is subjective.  They are:
  • Criticism
  • Comment
  • News reporting
  • Teaching/Scholarship
  • Research
  • Parody

However when it comes to the four more specific court related requirements, the primary criteria (In our view) is…the purpose and character of the use, including whether it is commercial or non-profit.  Here purpose and character can mean does the use transform the work by adding new meaning, messaging or expression or does it use the work for a different purpose than the original.  An example might be the critique of a painting, which would be a different use of the artwork than the artist intended. We note that while non-commercial uses are typically favored over commercial use cases, commercial use is not categorically infringing.  There is also the ‘public benefit’ consideration, along with a bit of hunting for ‘good faith’, meaning is the user willing to attribute the works even if they are fair use and don’t require it?.
The nature of the work is also a big factor. Is it factual or creative, with factual works having less fair use protection (Facts are not copyrightable) as is whether the work is published or unpublished, as original authors are typically granted the right to be the first publisher of their works.  The amount of the copyrighted work to be used is also a factor and while there are no specific rules, less use gets you more fair use leeway, especially relative to the size of the work, and less use of the key points or heart of the copyrighted material also gets more fair use latitude.
The last major factor is the tricky one.  What is the effect of the use on the value of the copyrighted work or the value of the market overall?  Will the use of the work be a substitute for the work itself and therefore reduce the value to the author?  This includes the current and future markets and is a tacit test to see how directly this potential use competes with the demand for the original (copyrighted) version.  The more ‘transformative’ the use, the less competitive it is considered.
While we point to a number of key factors, this is a very nuanced topic and has been argued in the courts ad infinitum, so regardless of the ruling we show below, every lawyer worth his or her salt will argue that whatever precedent that has been set, does not apply in this case, and the facts must be evaluated specifically on their own merits, leaving definitive rulings to future generations.
Here is our summary of the ruling, as short and sweet as possible:
The case is a dispute between several authors and Anthropic AI, the developer of the Claude LLM model family.  The authors believe that Anthropic used their works to train their AI models without the permission necessary as they are copyrighted works.  The authors allege that Anthropic pirated some of the works, purchased others and scanned the pages into a ‘research library’.  The models were trained on various subsets of the pirated works and the library copies.
The judge ruled in Anthropic’s favor citing that the use of the works to train the LLMs was a ‘transformative’ event and qualified the use as a ‘fair use’.  The judge pointed to the fact that none of the works were ever provided to users and that statistically mapping relationships between text fragments is fundamentally different from copying.  He cited the fact that humans read and learn from copyrighted material, allowing them to create new works, just as an LLM might ‘read’ the text relationships and create something new.  The judge also allowed Anthropic’s book digitization, citing that it was a digital replacement of books already purchased or licensed, not the creation of new works or additional copies.
That said, the judge did not allow Anthropic to use pirated copies for its digital library as the use of the works for a ‘central library’ was not a fair use, while the training was.  Anthropic made the case that pirating the works was ‘reasonably necessary’ for training the LLMs but was unable or unwilling to show which specific works were used in  training as opposed to those put in the library.  The judge did not buy that argument.
All in, while the headlines might rack the ruling up as a victory for the AI developers, it will more than likely be appealed and continue through the courts for years.  With many other cases pending, there will be no shortage of rulings for both sides until there is enough specific case law that the courts don’t have to cite fair use cases from the days before there were AIs.  The question remains however, what is to stop anyone from using copyrighted material to train an LLM when the US is in a race to develop AI models faster than our rivals?  In this case there are no indigenous tribes that have to be ‘relocated’ to mine the land or drill the oil, just a few writers who won’t be able to cash in on the AI boom as easily as they thought.  How is that going to hurt anybody? 
It won’t unless you happen to be the author who spent years writing with the hope that his/her works might mean something to somebody.  It won’t unless you composed a unique melody that could become a song we remember significant life events by, and it won’t unless you happen to be the painter who trained for years to be able to tint the sky in a way never done before.  All it takes is “Hey Gemini, create a song just like that one that I just played and post it to my Insta account” and the minutes , hours, days, and weeks that went into the creation of that original song you just heard is now a set of millions of relationships.  Those relationships can be used to create a song just a bit different from the one you just heard, in a few seconds.  Some folks say that’s a plus, we don’t.

Panel sales this year have been an up and down situation. January and April have been down roughly 12% each m/m, while March and May have been up by roughly the same amounts (February was up slightly).  On a cumulative basis against the same period last year, panel sales are down 1.7% and looking at only those that produce large panels, sales are down 2.4% y/y.  This comes after a relatively strong May, where sales were up 11.8% m/m but still down 10.7% y/y.  2024 saw most of the strength in panel sales in 2Q and 3Q so this year the industry will face those more difficult comparisons, although the tariff situation has made predictions as to monthly performance almost impossible.  That said, we expect June panel sales to be weaker as we expect TV panel prices to decline along with brand demand, and that weakness to carry into August unless some unusual US tariff situation develops when the most recent postponement expires in early July.  We estimate that TV panel sales currently make up 50% of total panel sales value, so a downward shift in TV panel pricing and or demand has a significant effect on overall industry panel sales value.

The  table below shows the m/m change in panel sales for each supplier for May, the y/y change, and the cumulative y/y change that shows where we stand this year at this point in time, compared to last year.  Those highlighted in red are primarily large panel producers.

​As we mentioned last week, we took a Q&A session that we did in March with 8 LLMs and resubmitted the same questions to the same LLMs again on Friday.  The idea was to see how much the AI’s had developed over this ~90 day period, particularly to see if one AI stood out.  While the answers were the meat of the study, we collected a considerable amount of data that helped put the results in perspective and as we sort through the 75 pages of data, we will pull out a few tidbits.  We note however that these questions were designed to be quite different from each other and should therefore register differently with each of the AI/LLMs, so it is not surprising that a particular AI might do well on one question and poorly on another.  That said, the thrust was really to see if and how much improvement the AI’s made over their original answers.  Sort of a re-test…
Some of the data consists of word counts.  We tracked answer word counts in conjunction with improvements or regression in the answers to see if the AIs became more succinct in their answers and how that correlated to correctness, the ultimate goal.  Here is a taste of what we found (more to come):
Here are the AI’s we queried.  Please note that some are more forthcoming as to their model and version, while others are not.  Microsoft’s (MSFT) Co-Pilot was the least willing to give such information, stating that it was developed by Microsoft and nothing else, while others were quite specific.
Gemini              Google (GOOG)          Flash/Pro 2.5
Claude              Anthropic (pvt)           Sonnet 4.0
MetaAI              Meta (FB)                      Non-specific Llama model
Co-Pilot            Microsoft                       Unknown
ChatGPT          OpenAI (pvt)                GPT-4 Turbo
DeepSeek        DeepSeek (pvt)          V3
Perplexity         PerplexityAI (pvt)       GPT-4o/Claude Sonnet 4.0
Grok                  xAI (pvt)                         3
We note also that the questions asked last week were identical to those asked in March and the only changes to what the AI responded was to remove lead-ins to further questions when they were irrelevant.
Here is Question #1:

1. What does ‘She’ sell and where does she sell them?

The question is derived from a nursery rhyme/ tongue twister inspired by a 19th century British fossil collector, Mary Anning and put to music and lyrics by Harry Gifford and Terry Sullivan in 1908.  The idea was to present no context with the rhyme to see if the AI were able to discern its origin, its point, or anything else about the song.  As it turned out, in the most recent query, DeepSeek was able to understand the reference, making a large improvement from the March query where it was unable to understand the reference at all and did not present an answer.  Grok also took a step forward after mistakenly assuming the reference might be concerning a specific person, brand, or company (specifying “Shein”) in its original response, and was now able to state that the phrase is a “well-known tongue twister linked to Mary Anning…”.  Grok did add that it could also be referring to a remote sales program by Shelby Sapp called “She Sells” but certainly credit must be given for the correct answer regardless of the add-on.
Meta stated that “Without more context, it's hard to pinpoint exactly what "She" sells or where.” (zero credit) with a similar response in March and Co-Pilot and ChatGPT did the same both times, each slightly differently.  Most surprising was Claude’s current response, which was “I need more context” as in the March query Claude was the only AI that identified the rhyme.  Gemini was also unable to answer without more information, although in March Gemini speculated that “she” can refer to various individuals engaged in reselling. Therefore, "she" can sell a wide variety of items in different locations, including:…and went on to list a large number of possible clothing items, handmade items, or accessories, so it would seem worse that Gemini came up with no answer this time, when it at least speculated a bit last time.
In terms of word count, it would seem logical that those unable to come up with an answer would see the number of words used decline from March, or at least stay the same, and that was the case overall, as the total number of words in the responses for question one declined by 23.3% relative to March totals.  The anomaly was Co-Pilot, who was unable to come up with an answer either time but saw its word count increase by 13.3%.  DeepSeek, one of two to correctly answer question 1, saw its word count increase by 33.1% as it produced a relevant answer, however Grok was also able to produce the correct answer and saw its word count decrease by 23.3%, essentially saying more with less words.
With two AIs improving, two declining, and the rest remaining unable to answer the question, when it comes to question #1, little progress has been made overall.  We have 9 other questions, each with their own characteristics, and results that are quite telling, so there is plenty more to come over the next few days including a summary of the data and a conclusion.  As we sift through the data, we note that some of the questions require a more qualitative view, such as question #9 which requests the Ais to “Create a 12-line poem about a grandfather clock in the style of Edgar Allen Poe”, which we compare to the poems written in March.  We are not educators nor critics, but the differences are more than obvious in many cases, as they are also obvious in some of the other questions.
Most interesting was question #3 which we took from our display work.  It was a complex question that required both math and logic and had a two part answer.  Given that depending on the number of places the calculations could be taken out to, there can be some variation to the correct answers for the 2nd part, but part 1 was all or nothing.  In March, 6 of the 8 AIs correctly answered part 1 of question #3 and two answered part 2 correctly (some were close), while in June 7 of 8 correctly answered part 1 and 4 answered part 2 correctly, although all but one was within the ballpark.  It would seem that math scores have improved a bit over the last few months, although we have another math question to tally.
While we hear almost daily how AIs are improving and we are edging closer to AGI, the reality of AI on a day-to-day basis seems to have a much shorter trajectory and quoted benchmarks seem less relevant.  When we complete the data from our Q&A we will try to present an honest picture of how things for the average AI user might have changed during the last quarter and will try to establish a quarterly check as to how our AIs are improving or regressing.  It’s not about benchmarks when you are sitting in a presentation and it turns out your AI was incorrect on the most recent figures you just presented.  Benchmarks won’t save you from “Mr. Carson wants to see you in his office. Now!” call.

Our concern for the CE space has been that tariff issues, particularly in the US, have pushed brands to pull-in production to avoid potential tariff deadlines.  This has caused on-shore inventory levels to climb at a time when demand was flat to down slightly.  While some of the less onerous CE tariffs have remained, the concern for brands is that another deadline is approaching in July, and it will be difficult to manage additional pull-ins on top of what exists.  During the 1st half of the year large panel prices have increased by 1.3% while small panel prices have declined by 2.9% for a total panel price (lg. & Sm.) increase of 1.0%.  The breakdown by panel type is included in our monthly panel price table below:

While TV panels have been the weakest category of late, panel producers are struggling to maintain prices in other categories.  TV set brands are working against higher basic costs and possible further tariffs and have been pushing for lower panel prices to offset these increases while reducing yearly targets.  June saw TV set brand order reductions impact panel prices for the first time since last August, and unless a tariff truce of some sort is called in July, we expect this lower demand level will be maintained until mid-August.

We have been tracking Samsung Electronics (005930.KS) Premium TV set pricing since they began marketing Mini-LED/QD sets in 2023 and their OLED lines since 2022.  The purpose is to compare the short and long-term pricing trends for particular TV set lines and for a more general view of Samsung’s premium TV set pricing on a year/year basis.  This gives us a monthly, quarterly and yearly trend that can help to understand how the company, which is the largest TV set producer globally, views the TV set market at any given time.
On a short-term basis, Samsung has been consistently following pricing pattern trends with both this year’s (2025) line and last year’s, as shown in Figure 1, with both year’s pricing moving in close synchronization.  That said, when we compare the rate of change in TV set pricing for the first 90 days that each line was available to consumers, one can see that this year has been quite different than previous years.   Each year since the Mini-LED/QD and OLED lines have been available, the price of each set category has declined during the first 90 days of avaialability, except this year, where prices have increased for all Mini-LED/QD categories and remained relatively flat for OLED types.  There have been ups and downs, typically holiday based, but the 90 day trend this year is certainly different than in previous years and would indicate a focus for Samsung more toward profitability than unit volume growth, at least in the Mini-LED/QD set lines.
The competition in the Mini-LED LCD TV space has continued to intensify, with Chinese brands, particularly Hisense (600060.CH) and TCL (000100.CH) expanding their lines with larger size models and more aggressive pricing, and with additional help from the Chinese government’s “New for Old” subsidy program, Samsung and other non-Chinese brands face considerable price competition, which tends to push Samsung’s general TV set positioning more toward higher-end premium sets, where there is a bit more margin flexibility.
In the US, Samsung has a considerably better position, with Chinese sets facing higher tariffs limiting competition from Chinese brands, which we expect has given Samsung the chance to keep premium TV set prices higher than normal during the early part of the year.  But as the year progresses, Samsung will have to begin the process of bringing down set prices to stimulate sales volumes.  If Samsung is to meet its goal of becoming the world’s largest OLED TV vendor, it will be necessary to bring OLED pricing more in line with seasonal norms, and while we are unsure if Samsung has similar goals with its Mini-LED/QD lines, we expect the same pricing issues will exist for those lines.

In the most recent 30-day period, Samsung’s premium TV set pricing has moved as follows: