● NVIDIA Dark Secrets-Three Near-Deaths-CUDA Monopoly-AI Supply Squeeze-2025 Shockwave
NVIDIA “6 Secrets Nobody Knew” Re-reading the 2025 AI & Global Economic Outlook: How Did This Company Nearly Go Under Three Times and Still Become #1 by Market Cap?
Today’s post includes all of the following.
① The three moments when NVIDIA was truly “on the verge of collapse,” and the high-stakes moves it chose each time
② Where the “turning points” were that transformed it from a gaming company into an AI infrastructure company (centered on years/events)
③ Why CUDA wasn’t just a technology, but exploded into a “platform economy”
④ The bottlenecks and beneficiary axes in the “AI semiconductor supply chain” that investors must watch in 2025
⑤ NVIDIA’s real moat that the news doesn’t explain well (it doesn’t end even if competitors catch up)
1) News-style timeline: The “6 secrets” that made NVIDIA’s success (centered on key events)
Secret 1. “Total failure of the first product (NV1) → the company almost disappeared”
In 1995, the first product NV1 was, for all practical purposes, a complete flop in the market.
It missed on price, compatibility, and market demand all at once, and it’s said they were down to the level of having only about six months of cash left.
The important takeaway here is that it learned early, in a painful way, that “even if the technology is good, if you can’t attach to the market standard and ecosystem, you’re finished.”
Secret 2. “SEGA ‘lifeline’ investment: it admitted failure and still won the next round”
Jensen Huang acknowledged internally, “We were wrong,” and secured survival funding by holding onto SEGA.
The lesson at this stage isn’t simply luck, but that in a crisis it changed the structure by securing both “cash flow + a partner” at the same time.
Secret 3. RIVA 128: it earned “market validation” with 1 million units in 3 months
In 1997, the hit RIVA 128 proved that “dedicated graphics chips are necessary.”
From this point, NVIDIA moved close to turning profitable, and it led all the way to its IPO (1999).
In other words, it wasn’t “technical conviction,” but “sales volume” that changed the narrative.
Secret 4. GeForce 256 & the word “GPU”: it changed the market’s language
In 1999, with GeForce 256, it put the term “GPU (Graphics Processing Unit)” front and center.
At the time it was criticized as marketing, but as a result it effectively solidified “a structure where a GPU sits next to the CPU” as an industry standard.
This later became the psychological/industrial foundation for the AI era, where “the GPU becomes a default component of the data center.”
Secret 5. After the dot-com bubble burst, a “bargain acquisition of 3Dfx assets”: panic became opportunity
In the early 2000s, its stock fell by nearly 90% due to the dot-com bubble, but as competitor 3Dfx was pushed to the brink of bankruptcy, NVIDIA absorbed its assets cheaply.
This wasn’t a simple M&A deal, but a textbook case of “buying technology, talent, and IP in a downturn to prepare for the next cycle.”
In today’s terms, it was a case of preempting supply chain and talent during a recession.
Secret 6. 2006–2016 “CUDA: 10 years of loss-like investment”: nobody understood it, but it stayed the course
This section is the most important part of the original text.
The stock moved sideways, and even internally people complained, “Weren’t we a gaming company?” but Jensen Huang poured money into CUDA to turn the GPU into a “general-purpose computing platform.”
In the end, the structural fit—that deep learning’s core is “matrix operations,” and the GPU’s strength is “parallel computation”—exploded in 2012–2016 and flipped the game.
2) The three decisive triggers that made NVIDIA “the center of AI”
(1) The 2012 AlexNet shock: “two gaming GPUs turned academia upside down”
The University of Toronto team (the Geoffrey Hinton lineage) delivered overwhelming results in the ImageNet competition, and the fact spread that they used two GPUs (GeForce GTX 580).
Here, NVIDIA realized something.
“That AI is decided not only by software but by hardware architecture (parallel computation).”
(2) The 2016 surge in data center revenue: why cloud companies bought “gaming chips”
As cloud operators like Google, Amazon, and Microsoft bought NVIDIA GPUs in large volumes, NVIDIA’s identity changed.
Wall Street’s frame of viewing it as a “gaming company” broke, and a re-rating began as an AI infrastructure company.
This trend started before today’s generative AI boom.
(3) Even after the 2018 crypto collapse, “the organization didn’t wobble”: internal conviction was different
As GPU demand swung with the crypto boom/bust and the stock price also shook significantly, testimonies say the company internally didn’t stagger like it used to.
This is a very important signal.
Because it means it had transformed into a company living off a long-term structure (data center AI), not short-term demand (coins).
3) From a global economic outlook perspective: what changed in the market as NVIDIA rose
① Interest-rate hike/easing cycles and tech-stock valuations
Tech stocks tend to see valuations compressed during rate-hiking cycles, and receive premiums again as expectations for rate cuts grow.
NVIDIA has also reacted strongly to this flow, not only to “earnings.”
Especially after generative AI, AI capital expenditure (CAPEX) has started to be treated like real-economy investment, giving it an infrastructure-stock character beyond a simple growth-stock identity.
② Inflation and power/data center costs: AI is an “electricity-eating industry”
The most realistic constraint that can slow AI adoption more than expected is electricity and cooling, and the speed of data center construction.
In other words, it’s not only a semiconductor problem; power infrastructure and construction/equipment costs can create a ceiling for AI growth.
This point is easy to miss when the news emphasizes only “chip performance.”
③ U.S.–China tensions and the reshaping of the AI semiconductor supply chain
AI semiconductors are directly affected by regulations and export controls.
So NVIDIA has become a company that must manage geopolitical risk through its product lineup and region-by-region sales strategy, not just a company that makes good products.
This will likely remain a factor that increases stock-price volatility going forward.
④ Global supply-chain bottlenecks (foundry/HBM/packaging): “NVIDIA can’t ship everything it wants just because it wants to make it”
These days, the AI semiconductor supply chain doesn’t end with a single GPU.
HBM (High-Bandwidth Memory), advanced packaging (CoWoS-type), substrates/power components all have to line up at the same time for shipments to happen.
So from an investment perspective, you need to track not just “NVIDIA alone,” but the entire AI semiconductor supply chain to grasp the flow.
4) The “most important core point” that other news/YouTube rarely says (my viewpoint summary)
Core point 1) NVIDIA’s moat is not “chip performance” but “developer time”
A lot of content fixates only on “NVIDIA GPUs are fast,” but the real moat is the code, tools, and workflows developers have already accumulated in the CUDA ecosystem.
Even if a competitor delivers similar performance, for companies the cost of “rewriting existing code” is too large.
This is classic platform-economy lock-in.
Core point 2) NVIDIA is positioning itself not as a “product company” but as an “AI factory architect”
Now it doesn’t just sell GPUs; it provides the entire system for producing AI in data centers (networking/software/development environment) bundled as a package.
If this strategy works, pricing power moves beyond chip unit price to “AI production unit cost.”
In other words, the structure can justify not a simple semiconductor-company valuation, but an infrastructure-platform valuation premium.
Core point 3) Why a company that has gone through multiple crashes is strong in the AI era
The 70–90% plunge experiences mentioned in the original aren’t just dark history; they built “operational capability to survive in a cyclical industry.”
AI semiconductors are likely to see repeated cycles of oversupply/shortage in the future, and the companies that survive will be strong not only in technology but also in inventory, production, and partnership operations.
5) 2025 checklist: what should you watch in NVIDIA/AI trends?
A. Demand-side (cloud & enterprises) indicators
Changes in AI CAPEX guidance from cloud companies (increase/maintain/decrease).
The speed at which AI services “convert into revenue” (experimentation → commercialization).
B. Supply-side (bottleneck) indicators
HBM supply and pricing, advanced packaging capacity, power/data center construction speed.
C. Macro indicators (high sensitivity for stock prices)
How U.S. inflation and employment reshape the rate path (directly tied to tech-stock valuations).
Updates on U.S.–China regulations (export controls/circumvention rules, etc.).
< Summary >
NVIDIA was not a company that succeeded smoothly from the start; after its first product failed and cash nearly ran out, it survived with SEGA’s investment and then opened the market with RIVA 128 and GeForce 256.
After the dot-com bubble burst, it absorbed 3Dfx assets and survived, and from 2006–2016 it burned 10 years on CUDA to complete “GPU = AI computing platform.”
The turning points were the 2012 AlexNet moment and the 2016 surge in data center revenue, and in 2025 the key variables are AI semiconductor supply-chain bottlenecks (HBM/packaging/power) and interest rates/geopolitics.
The real moat is not chip performance, but developer lock-in created by the CUDA ecosystem, and a platform strategy that sells up to the AI factory (systems).
[Related posts…]
- After NVIDIA became #1 by market cap, the next phase of the AI infrastructure war
- Lock-in created by the CUDA ecosystem: why competitors can’t catch up
*Source: [ 월텍남 – 월스트리트 테크남 ]
– 아무도 몰랐던 엔비디아의 비밀 6가지
● CES 2026 Hype Dead, AI Goes Invisible, Pre-Booked Buyer Deals Win
CES 2026, “Is It Now Meaningless?” The Viewing Points That End the Debate: This Year, Not an “AI Show” but a “Go-to-Market Blueprint” Will Decide Results
This article includes exactly three things with absolute clarity.
① I structurally organized why the “CES is useless” argument keeps repeating, and the root cause is not a platform issue but a “lack of purpose.”
② I break down why Korean companies “win lots of Innovation Awards at CES but are weak on revenue/contracts,” from the perspectives of buyer movement paths, data, and pre-show.
③ And something other news/YouTube rarely talks about: the shift in CES participation objectives from sales → marketing → communication/relationship design is the core point of the 2026 performance strategy, and I highlight it separately.
1) CES 2026 News Briefing: This Year’s Viewing Core Point Is Physically Confirming “Where AI Is Hidden”
CES is not an industry-specific trade show that sells only one sector; it has a strong character as a “comprehensive exhibition platform” where technologies from multiple industries mix in one place.
That’s why it’s great for seeing how horizontal technologies, rather than vertical technologies, create “cross-industry connections.”
The point emphasized by Lee Dong-gi (former COEX CEO/advisor) in the original source is simple.
If 2024 was “AI Everywhere (emergence),” 2025 was “deepening,” and 2026 is the year to confirm scenes where AI “enters everyday life more deeply and becomes more advanced.”
1-1) Why AI “Isn’t Visible” at CES, and the Exhibition Challenge for 2026
AI isn’t a visible machine; it’s software/decision-making/automation logic, so even on-site you can get the feeling, “They say everything is AI, but where is the AI?”
So the key for 2026 is “how to make invisible technology visible (demo design).”
1-2) Why CES Still Matters: The “Purchasing Power” of the U.S. Market and Buyer Density
CES is not just an event for seeing trends; the core explanation is that it’s a place to confirm on-site “what gates you must pass through to enter the U.S. market.”
The U.S. has a small share of the global population but a large share of the consumer market, and above all, major distribution/platform/retail buyers truly show up in huge numbers.
The real point in the original source is powerful.
CES releases attendee data every year, and from Amazon alone, roughly 1,660 people attend, and Walmart/Best Buy and others also visit in groups ranging from dozens to hundreds.
The essence of CES’s value is, “Where else can you meet these people all at once?”
2) The Reality of the “CES Is Useless” Claim: CES Didn’t Weaken; Participation Methods Are Outdated
Big tech companies like Apple and NVIDIA focus more on their own events (WWDC, GTC, etc.), and Samsung also rents hotels to hold exhibitions/meetings in separate formats instead of the main exhibition hall.
Seeing this leads people to say, “CES is over,” but the conclusion in the original source is the opposite.
The problem isn’t the CES platform; it’s participation that is “just being there” without purpose and preparation.
2-1) Why Korean Companies Win Many Innovation Awards but Have Low “Practical Results”
On-site, they focus on explaining the technology as “the world’s first/best,” but the factors buyers use to decide purchases go far beyond technology.
Pricing policy, distribution/channel strategy, tariff/regulatory risk, after-sales service, and the structure of local partnerships are all included.
In other words, an Innovation Award is only a leverage point for “awareness/trust,” and actual contracts move only when there is a “market entry package.”
What matters here is the advice: “Use the exhibition as a place to collect feedback and validate conditions.”
3) CES 2026 Performance Strategy: The Decisive Factor Is Not “Booth Operations” but “Pre-show Design”
The most realistic advice was this.
If you view an exhibition as a “one-time event,” you get almost no results; you must run pre-promotion around the exhibition and lock in buyer meetings “before they even arrive at the venue” to produce results.
3-1) The Data Is Already Public: Move Only After Seeing “Who Is Coming”
CES publishes attendee/company data.
But the issue is that many exhibitors “don’t know they’re coming and can’t make them come to my booth,” as pointed out.
In summary, the strategy has three steps.
① Define the highest-priority targets our product should meet (retail, platform, manufacturing, investment, media).
② Check through data whether those targets are attending CES.
③ In the pre-show stage, “reserve” meetings, and on-site, connect through demos/negotiation/follow-up actions.
3-2) Change the Participation Objective: Moving From “Immediate Sales” Toward “Relationship/Communication Design”
This is the sharpest shift in the original source.
The role of exhibitions used to be “sales,” then it became “marketing,” and now it is shifting in function to “communication/exploration of customer relationships.”
This shift is extremely important for Korean companies.
Because if you go in “let’s sign a contract at this CES” mode, disappointment per cost grows,
but if you go with “let’s validate the conditions for entering the U.S. market (price/tariffs/distribution/after-sales/partners) on-site and lay the relationship groundwork,” the ROI feels completely different.
4) From a Startup Perspective: CES Is the Best Testbed for Finding PMF (Product-Market Fit)
Because CES mixes people from many industries all at once, it’s easy to discover that real responses come not from the initially targeted market (A) but from markets (B/C).
That can become the trigger for a pivot.
In particular, use startup zones like Eureka as a stage to “get feedback and explore the market,”
and afterward, it’s more efficient to find “specialized trade shows” that fit your industry and participate continuously, according to the advice that follows.
5) Is a “Korean-Style CES” Possible: The Conclusion Is “Who Comes,” Not “Scale”
Every year there’s talk about creating a CES-level exhibition in Korea, but the key is not the scale of the exhibition but the “visitor composition (buyers/investors/media).”
The reality is that it’s difficult to get global buyers to come to Korea at the same level as CES.
However, for exhibitions in areas like batteries/automation/food, many foreign buyers do come to Korea,
and opinions were also presented that competitiveness can be built by expanding exhibition infrastructure and fostering exhibitions over the long term.
6) What Big Tech’s “Exit From CES” Means: CES Didn’t Weaken; “Exhibition Formats Are Splitting”
The trend of large companies using hotels/separate spaces instead of the main exhibition hall for customer-centered exhibitions
can be interpreted as a signal that “high-density meetings with target customers/partners” have become more important than showcasing to an unspecified crowd.
If Korean companies reference this directly, it changes like this.
The moment you switch from a “booth traffic” KPI to a “decision-maker meetings” KPI, the strategy changes.
7) The Direction of Future Exhibitions: Why Offline Exhibitions Grow Even in the AI Era
It may seem like offline exhibitions would die as AI and digital transformation accelerate, but in reality, exhibitions have been doing even better after COVID, as mentioned.
The reason is three things online cannot replace.
① Serendipity: the moment of discovery where you pass by and think, “Huh? What is this?”
② Multi-sensory experience: the lasting impression of touching, seeing, and directly feeling something
③ Face-to-face: trust/speed/impact created by real meetings
John Naisbitt’s “High Tech High Touch” fits exactly in this context.
The more technology advances, the more people seek “touch” and relationships.
8) The “Truly Important Content” Other YouTube/News Rarely Covers (Only the core points, Separately Summarized)
This is where the point is.
It’s easy to attribute poor CES results to tired lines like “Korean companies can’t speak English” or “their marketing is weak,”
but the essence presented in the original source is far more structural.
1) CES Is Not an “Exhibition” but an “Outpost for Entering the U.S. Market”
It doesn’t end with just showing the product at the show floor;
you must use it as a place to confirm how to place your product onto the U.S. commercial system, including tariffs/distribution/pricing/after-sales/partnerships.
2) Even Though Data on “Who Is Coming” Is Public, Most Don’t Use It Strategically
It’s not that buyers aren’t coming;
results don’t happen because there is no design that makes buyers “come to my booth.”
3) The Purpose of Exhibitions Has Changed: If You View It Through Sales KPIs, the Probability of Failure Increases
Exhibitions are moving toward communication/relationship/feedback-based strategy building,
but Korean companies often still set expectations around “on-site contracts.”
That mismatch creates the problem.
4) For AI, the Ability to “Make It Visible” Is Competitiveness
More than the AI technology itself, “the exhibition capability to physically construct demos/stories/usage scenes” determines success or failure.
In other words, technical capability + exhibition production capability (use-case visualization) must go as one package.
< Summary >
CES 2026 is not about it being meaningless; the problem is “participation without purpose.”
Because AI is invisible, 2026 is the year to prove everyday application through “physical demos.”
Results are decided not by on-site booth operations but by pre-show promotion and buyer meeting reservations.
An Innovation Award is only a starting point; contracts require a market entry blueprint that includes pricing, distribution, tariffs, and after-sales service.
The function of exhibitions is shifting from sales to communication/relationship design, and for startups, it is the optimal place to explore PMF.
[Related Posts…]
- CES Participation Strategy: How to Deliver Results Through Pre-show Meetings
- AI Trends: Application Points to Confirm On-site in 2026
*Source: [ 티타임즈TV ]
– CES2026 관���포인트, CES에 가서 성과 내려면
● Warner Bros Takeover War, Netflix vs Paramount, CNN Power Grab, Trump Antitrust Bombshell
Why the Warner Bros. Acquisition Battle Is Really Fought Over CNN: Netflix vs. Paramount (Oracle + Middle East Money) + Trump Jumping In, and Why This Is the Opening Signal of a Media Industry Reshuffle
This case is not just a “Hollywood studio M&A.”
You have to look at these three together to see the flow:
① Whether this is a fight that further cements Netflix’s streaming dominance,
② Whether the Paramount–Oracle–Middle East capital bloc is trying to seize control by bundling “news (public opinion) + content (archives)” in one move,
③ And why Trump personally entered the arena by pulling the “antitrust” card,
Plus, the biggest variable is “who CNN ends up with.”
From here, it stops being entertainment and becomes, in effect, a game over the next presidential election and political communication infrastructure.
1) News-Style Briefing: What Has Unfolded So Far (Fact-Flow-Centered Summary)
1-1. Deal Structure: Netflix “Excluding CNN” vs. Paramount “Including CNN”
Based on the original text, Netflix is described as moving toward an acquisition agreement for Warner Bros. assets while “excluding the news division like CNN.”
By contrast, Paramount tried to shake up the board by saying it would buy everything “including CNN.”
From this point, the fight rapidly becomes politicized—not as an acquisition battle between content companies, but as a battle over the destination of a news channel.
1-2. Why It Turns Hostile: Price + Shareholder Persuasion + External Funding
Paramount is effectively setting up a classic hostile takeover scenario by offering a higher price and directly targeting shareholders.
When the structure shifts this way, “shareholder利益” moves ahead of “management agreement,” negotiations drag out, and the deal becomes far more sensitive to regulatory and political variables.
In other words, the market sees the deal entering a zone where it cannot run on “economic logic” alone.
1-3. Trump’s Entry Point: “Antitrust” as the Pretext, “CNN” as the Practical Gain
In the original text, Trump signals intervention on the grounds that if Netflix takes Warner Bros. as well, its market share would grow and antitrust issues could arise.
But the key takeaway of this game is not simply “containing Netflix” itself,
but the interpretation that the real crossroads is whether CNN remains progressive-leaning or shifts into the conservative camp.
Ultimately, “regulation (antitrust)” is the blade, and the “public-opinion channel (CNN)” is the target.
2) “Why Warner Bros. Is Necessary” by Player (Reinterpreted Through Economic Logic)
2-1. Netflix: The Weak Spot Is “Archives,” and Warner Is a 100-Year IP Warehouse
Netflix is unrivaled in streaming operations, recommendation systems, and global distribution,
but it has long faced criticism that it is relatively weak in “classic libraries (archives) built up over time.”
Warner Bros. has long-lived IP like Harry Potter and Batman, plus a 100-year library—a “subscriber-retention device.”
If it acquires this, Netflix can reduce churn (watch time ↑) and raise rates more easily in its ad-supported tier (AVOD) as well.
This is a typical “IP-driven cash-flow strengthening” strategy.
2-2. Paramount (Oracle Line): Merge Studios to Become “Hollywood Number One” + Add News Too
If Paramount absorbs Warner as well, production capabilities, distribution power, and the library all expand,
creating what the industry calls “economies of scale.”
In particular, the original text mentions Oracle founder Larry Ellison (and his son David Ellison),
and there is an underlying picture of that line trying to expand film and media influence through Paramount.
And it matters that Paramount already owns CBS.
Add CNN on top of that, and it becomes possible to design a media empire that bundles “entertainment + news” into one unit.
2-3. Middle East Oil Money (Sovereign Wealth Funds) + Kushner Network: Not “Financing,” but a “Political-Economic Alliance”
The original text mentions flows of money from Saudi and UAE sovereign wealth funds entering the deal.
If you see this only as “investment from places with lots of money,” you see only half.
In reality, it should be viewed as a structure where political and media power inside the U.S. combines with global capital.
This also explains why “media influence in an election cycle” can create a deal premium.
3) The Signal It Sends to the Market: This Is Not “Streaming Competition,” but a “Media-Chain Restructuring”
3-1. Traditional Media vs. Platform Media: The First Battle Is Warner; the Next War Is YouTube and TikTok
The original text also introduces the view that “this is the first battle,” with a larger war still ahead.
The key takeaway is that Netflix/Paramount-style “high-cost production and programming models”
must compete with YouTube/TikTok-style “low-cost, high-volume creator models.”
So right now, it is a phase of building “baseline stamina” by first controlling the library (the past) and streaming distribution (the present),
in order to move into the next stage: AI production and personalized distribution (the future).
3-2. Antitrust Regulatory Risk: “Political Sensitivity” May Matter More Than “Market Share”
On the surface, antitrust issues are mentioned,
but because this deal includes the politically sensitive asset of a news channel (CNN), regulators and politicians may respond more actively.
In other words, unlike a typical M&A where “price matters most,”
the risk premium may attach to “who buys it and how large the societal fallout is.”
In a case like this, volatility is unavoidable from an investor’s perspective.
3-3. Why the U.S. Media Camps Have Turned Into a Free-for-All: The Misalignment of Culture (Hollywood) vs. Politics (Elections)
Hollywood tends to lean progressive overall,
but Netflix also receives backlash as a “tech platform” that has disrupted the traditional production ecosystem.
Conversely, Paramount presents itself as a traditional studio,
but politically it is drawn into controversy as connections to Trump/the conservative camp are discussed.
That is why the industry and the press produce contradictory reactions like “politically I dislike A, but industrially A is advantageous.”
4) AI Trend Perspective: Where This Acquisition Battle Connects to “AI Media”
4-1. The Real IP Is Not “Video Originals,” but “Trainable Rights + Archive Data”
The reason content companies’ valuations are rising is not simply because they have many masterpieces,
but because they can run remakes, spin-offs, game adaptations, and short-form repackaging based on those masterpieces.
And when generative AI enters this process, the cost structure of production itself changes.
The side that holds a Warner-scale library gains overwhelmingly more “reusable assets” in the AI era.
4-2. CNN’s AI Use Is Less About “Production Efficiency” and More About “Agenda-Setting and Distribution Optimization”
In news, production efficiency matters more than in film, but the more fundamental value is “distribution optimization” and “agenda-setting.”
If AI enables personalized recommendations, automatic clip creation, and message variations by region and generation,
a news channel can function essentially like a “political marketing platform.”
That is why CNN’s ownership grows beyond editorial direction alone,
and expands into the issue of holding the key to communication infrastructure in the AI era.
4-3. Why the Oracle Line Is Mentioned: The Combination of Cloud, Data, and Media
Oracle is not an entertainment company; it is a data and cloud-based company.
If the Oracle network expands its influence into media,
a scenario becomes possible in which content production (studio) + data infrastructure (cloud) + distribution/advertising (platform) are bundled as one set.
This is less a simple M&A and more a reassembly of the media value chain in the AI era.
5) The “Most Important Point” Others on YouTube/News Often Miss (Separate Summary)
First, the killer asset in this deal is not “Warner films” but “CNN’s agenda-setting power.”
Content can be bought with money, but once a public-opinion channel is captured, it is hard to replace.
Second, the antitrust frame can function as a “regulatory lever” to stop Netflix.
The real risk may be less about market-share numbers and more about social resistance and political burden around owning a news channel.
Third, Middle East sovereign wealth fund money may be a long-term position that binds “global capital–U.S. politics–media,” rather than a simple investment.
This structure will likely appear more frequently depending on U.S. economic uncertainty, interest-rate shifts, and dollar liquidity flows.
Fourth, the destination of this fight is not “number one in streaming,” but “who secures more AI-reprocessable IP + data.”
In the end, the more generative AI raises content productivity, the more the value of source IP/archives rises.
6) What to Watch Going Forward (Checklist)
– Whether CNN will be separated (spin-off) from the deal or integrated while included
– The intensity of antitrust regulatory review: whether the focus is on “streaming market share” or “news influence”
– Paramount’s financing structure: changes in the participation share of sovereign wealth funds/large investors
– Post-acquisition plan: global repackaging of the library (ad-supported tiers, sports/news bundling, short-form expansion)
– Adoption of AI production/editing/automated clipping: how much they invest not in cost reduction but in “distribution control”
< Summary >
The Warner Bros. acquisition battle is not “Hollywood M&A,” but a political and public-opinion infrastructure fight over CNN’s ownership.
Netflix seeks to strengthen streaming competitiveness with a 100-year archive (IP), while Paramount seeks to expand influence by bundling CNN on top of CBS.
Trump’s antitrust mention is the pretext, and the core point is CNN’s editorial direction and media power in the next presidential election cycle.
This deal is an opening signal showing how important “trainable IP + data + distribution” is in the AI era.
[Related Posts…]
*Source: [ 티타임즈TV ]
– 트럼프는 왜 워너브라더스 인수전에 발을 걸쳤나 (국제시사문예지 파도)
