Few recent software releases have been as hyped as OpenAI’s launch of its GPT-5 model. “GPT-5 is the first time that it really feels like talking to an expert in any topic, like a PhD level expert,” said CEO Sam Altman in a recent press briefing.
Is this new release as big of an upgrade as OpenAI claims? What do these changes actually mean for ChatGPT users? WIRED reporters are currently testing this newest drop from OpenAI, and seeing how GPT-5’s ability to write, code, and perform other tasks compares to past releases.
At our next subscriber-only livestream, we’ll be answering your questions about GPT-5 and the future of generative AI. Join us on Thursday, August 14, at 1 pm ET / 10 am PT / 6pm UK to hear from our expert panel featuring WIRED senior reporter Will Knight, who authors the subscriber-only AI Lab newsletter, and senior correspondent Kylie Robison, who authors the subscriber-only Model Behavior newsletter. Both reporters have been reporting on chatbots for years and closely following OpenAI’s developments.
Leave any questions you want the panel to address in the comments below! We’ll see you right here, on the WIRED website, live on Thursday.
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Early-stage venture firm A* on Tuesday announced a $450 million Fund III. The firm takes a generalist approach, backing companies across categories including AI applications, fintech, healthcare, and security. The average check size for this fund will be between $3 million and $5 million, with the aim to back at least 30 startups. The capital will be deployed over the next two to three years, as with the firm’s previous funds. Limited partners include nonprofits, foundations, and endowments; Carnegie Mellon University is among the publicly named backers.
A*, founded in 2020 and run by Kevin Hartz and Bennet Siegel, previously raised a $315 million Fund II in 2024 and a $300 million Fund I in 2021. Hartz is a serial entrepreneur best known for co-founding Xoom, the international money-transfer service PayPal later acquired for $1.1 billion in 2015, and Eventbrite, the event-ticketing platform that went public in 2018. Siegel came up through Boston Consulting Group and Altamont Capital Partners before spending four years as a partner at Coatue Management.
The firm has also drawn attention for backing unusually young founders, even as the practice has become more common since. Hartz told TechCrunch last fall that close to 20% of the firm’s current portfolio involve teenage entrepreneurs. Among others of its investments, it has backed the fintech company Ramp and the AI firm Mercor.
This story was updated to clarify the name of the firm.
Early-stage venture firm A* on Tuesday announced a $450 million Fund III. The firm takes a generalist approach, backing companies across categories including AI applications, fintech, healthcare, and security. The average check size for this fund will be between $3 million and $5 million, with the aim to back at least 30 startups. The capital will be deployed over the next two to three years, as with the firm’s previous funds. Limited partners include nonprofits, foundations, and endowments; Carnegie Mellon University is among the publicly named backers.
A*, founded in 2020 and run by Kevin Hartz and Bennet Siegel, previously raised a $315 million Fund II in 2024 and a $300 million Fund I in 2021. Hartz is a serial entrepreneur best known for co-founding Xoom, the international money-transfer service PayPal later acquired for $1.1 billion in 2015, and Eventbrite, the event-ticketing platform that went public in 2018. Siegel came up through Boston Consulting Group and Altamont Capital Partners before spending four years as a partner at Coatue Management.
The firm has also drawn attention for backing unusually young founders, even as the practice has become more common since. Hartz told TechCrunch last fall that close to 20% of the firm’s current portfolio involve teenage entrepreneurs. Among others of its investments, it has backed the fintech company Ramp and the AI firm Mercor.
This story was updated to clarify the name of the firm.
#Kevin #Hartzs #closed #fund #million #TechCrunchA* Capital,Kevin Hartz,Startups">Kevin Hartz’s A* just closed its third fund with $450 million | TechCrunch
Early-stage venture firm A* on Tuesday announced a $450 million Fund III. The firm takes a generalist approach, backing companies across categories including AI applications, fintech, healthcare, and security. The average check size for this fund will be between $3 million and $5 million, with the aim to back at least 30 startups. The capital will be deployed over the next two to three years, as with the firm’s previous funds. Limited partners include nonprofits, foundations, and endowments; Carnegie Mellon University is among the publicly named backers.
A*, founded in 2020 and run by Kevin Hartz and Bennet Siegel, previously raised a $315 million Fund II in 2024 and a $300 million Fund I in 2021. Hartz is a serial entrepreneur best known for co-founding Xoom, the international money-transfer service PayPal later acquired for $1.1 billion in 2015, and Eventbrite, the event-ticketing platform that went public in 2018. Siegel came up through Boston Consulting Group and Altamont Capital Partners before spending four years as a partner at Coatue Management.
The firm has also drawn attention for backing unusually young founders, even as the practice has become more common since. Hartz told TechCrunch last fall that close to 20% of the firm’s current portfolio involve teenage entrepreneurs. Among others of its investments, it has backed the fintech company Ramp and the AI firm Mercor.
This story was updated to clarify the name of the firm.
Counter-Strike 2 is a great demonstration of the finest economic systems of games created so far. In particular, such an economic system is represented by virtual trading of items worth more than $8 billion. Indeed, one should bear in mind that this is not a typo – this figure really represents the cost of items worth $8 billion. It may be added that this amount is larger than GDP in many countries, despite not having any effect on the gameplay. So, how did some in-game items attain such a multi-billion dollar economy and what fuels it? We will explain.
How a Digital Skin Gets Its Price Tag
Every skin in CS2 has a set of properties that determine its value, and understanding them is the first step to making sense of this economy.
Rarity tier is the most obvious one. Skins are categorized from Consumer Grade (white, the most common) all the way up to Covert (red, the rarest non-knife items) and Contraband (the ultra-rare category with only one item — the M4A4 Howl). Knives and gloves sit in their own Extraordinary tier, which is part of why they command such premium prices.
Then there’s float value — a number between 0.00 and 1.00 that determines a skin’s visual condition. A float of 0.01 means the skin looks virtually brand new (Factory New), while 0.85 means it’s scratched up and Battle-Scarred. Two AK-47 Redlines might look similar at a glance, but a 0.01 float Factory New will sell for significantly more than a 0.15 Minimal Wear.
And finally, there are pattern-based factors. Certain skins like Case Hardened and Fade have pattern indexes that produce unique visual results. A Case Hardened AK-47 with a full blue gem pattern can sell for tens of thousands of dollars, while the same skin with a standard pattern might go for $40. Doppler knives have distinct phases, each with its own pricing tier. Even sticker placements matter — a skin with rare Katowice 2014 stickers in the right positions can multiply the base price several times over.
The Marketplace Ecosystem
Here’s where things get interesting from a tech perspective. Unlike most games where you buy skins from a single in-game store, CS2 has an entire ecosystem of competing marketplaces.
Steam Community Market is Valve’s own platform and the default option for most players. It’s integrated directly into the Steam client, making it convenient, but it comes with a 15% transaction fee and locks your earnings in Steam Wallet — you can’t cash out to real money.
It resulted in the creation of an extensive array of third-party marketplaces, which include websites like Skinport, DMarket, CSFloat, Buff163, and countless other options. These websites allow users to exchange skins for real money, using various means of payment, such as PayPal payments, bank transfers, and cryptocurrency transactions. The fee structures on these websites vary considerably, ranging from zero percent up to 10 percent and beyond.
This price fragmentation is exactly why analytics and comparison tools have become essential for anyone who takes CS2 trading seriously. Experienced traders routinely check CS2 prices across multiple platforms before making a move, because the price gap between the cheapest listing and the most expensive one for the same skin can easily be 15-30%.
Market Cap Tracking — Like Crypto, But For Skins
One of the more fascinating developments in the CS2 economy has been the adoption of financial tracking concepts borrowed from traditional and crypto markets.
The total CS2 market capitalization — the combined estimated value of every tradeable item in the ecosystem — is tracked in real time, much like how CoinMarketCap tracks cryptocurrency values.At the end of 2025, the peak market capitalization of CS2 was more than $6 billion; however, the market capitalization dropped by roughly 30% in a single move when Valve made an update (to be discussed later).
Such advanced monitoring is essential for the user to see whether the general market is expanding or contracting. If there is an increase in the market cap, then demand and investments are likely increasing; otherwise, a sharp drop may indicate a Valve update, season, or a major event in the global gaming economy.
The data-driven platform collects information from over 20 marketplaces and provides dashboards that contain trend analysis, volumes, and price movements that could have been taken directly from a professional stock trading platform. The economy of CS2 has reached such a degree of development that the very concept of “gaming” becomes irrelevant.
Trade-Up Contracts: The Economy’s Built-In Upgrade Path
Valve didn’t just build a marketplace — they built game mechanics directly into the economic system. However, the most crucial part is the Trade-Up Contracts where the user gets a skin from the next level collection using ten skins from the current level collection.
Even though this concept seems quite simple, it requires rather complex mathematical calculations. Namely, the output skin’s type is dependent on the input collections’ types, whereas its float is calculated according to the average float of all input skins scaled to the output collection’s range. Thus, an advanced player may affect the probability of getting a certain skin via inputs manipulation.
To explain, if seven skins belong to one collection while three skins are from another, the output skin will most probably originate from the first collection. If the first collection contains a $500 skin at the next tier and the second contains a $30 skin, you can engineer a heavily weighted gamble in your favor.
But here’s the catch — the math only works if you actually run the numbers. The inputs might cost $80 in total, but if the expected value of the output is only $60, you’re making a bad bet regardless of the potential upside. That’s why experienced traders simulate their contracts using a CS2 trade-up calculator before committing any skins. These tools predict every possible outcome with exact probabilities, float projections, and expected profit or loss.
The trade-up system was further shaken in October 2025 when Valve added the ability to trade up Covert skins into knives and gloves — something that was previously impossible. Players could suddenly turn five Covert skins worth roughly $5-10 each into knives that were previously selling for $1,000+. The result? Knife prices crashed overnight, the total market cap dropped by hundreds of millions, and the entire pricing hierarchy had to readjust.
The Tech Infrastructure Behind It All
All that lies beneath all these graphs and calculations is quite a bit of technology. Real-time data feeds, APIs, and aggregators pull pricing information from several different marketplaces simultaneously.
Automated trading, monitoring services, portfolio management tools, and other such applications are developed by third parties using the marketplace APIs. Some platforms offer their own developer APIs with endpoints for price recommendations, market analytics, and cross-platform price comparison — essentially creating the financial infrastructure layer that the CS2 economy needed to operate at scale.
Steam itself provides API access for inventory data, market listings, and transaction history, which third-party services use to power everything from inventory valuation tools to automated trading systems.
The sophistication has reached a point where the CS2 economy has its own version of Bloomberg terminals — dashboards that track market-wide trends, individual item price histories, trading volumes, liquidity scores, and even volatility metrics. Professional traders monitor these tools the same way a Wall Street analyst watches stock tickers.
Why It Matters Beyond Gaming
The CS2 skin economy isn’t just a curiosity — it’s a case study in how digital ownership, market dynamics, and community-driven value creation work at scale.
This is what some of the main points which can be derived from this are. Firstly, scarcity defines value in all instances. It has been illustrated in the CS2 skins case study, in which it is clear that it does not matter whether items are tangible or useful in order for them to have economic value.
Second, platform decisions have outsized economic impact. Valve’s single update in October 2025 erased over a billion dollars in virtual item value. No other company has that kind of direct influence over a player-driven economy of this scale.
And third, the line between gaming economies and financial markets is dissolving. When your hobby comes with real-time price tracking, market cap analytics, trade-up calculators, and cross-platform arbitrage opportunities, you’re not just playing a game anymore. You’re participating in a micro-economy that happens to live inside one.
Whether you’re a casual CS2 player who’s never sold a skin or a veteran trader running profit calculations on every drop, the scale and sophistication of what’s been built here is worth paying attention to. An $8 billion economy that runs on cosmetic pixels, community trust, and a few really good APIs — that’s the kind of thing you only find in gaming.
Counter-Strike 2 is a great demonstration of the finest economic systems of games created so far. In particular, such an economic system is represented by virtual trading of items worth more than $8 billion. Indeed, one should bear in mind that this is not a typo – this figure really represents the cost of items worth $8 billion. It may be added that this amount is larger than GDP in many countries, despite not having any effect on the gameplay. So, how did some in-game items attain such a multi-billion dollar economy and what fuels it? We will explain.
How a Digital Skin Gets Its Price Tag
Every skin in CS2 has a set of properties that determine its value, and understanding them is the first step to making sense of this economy.
Rarity tier is the most obvious one. Skins are categorized from Consumer Grade (white, the most common) all the way up to Covert (red, the rarest non-knife items) and Contraband (the ultra-rare category with only one item — the M4A4 Howl). Knives and gloves sit in their own Extraordinary tier, which is part of why they command such premium prices.
Then there’s float value — a number between 0.00 and 1.00 that determines a skin’s visual condition. A float of 0.01 means the skin looks virtually brand new (Factory New), while 0.85 means it’s scratched up and Battle-Scarred. Two AK-47 Redlines might look similar at a glance, but a 0.01 float Factory New will sell for significantly more than a 0.15 Minimal Wear.
And finally, there are pattern-based factors. Certain skins like Case Hardened and Fade have pattern indexes that produce unique visual results. A Case Hardened AK-47 with a full blue gem pattern can sell for tens of thousands of dollars, while the same skin with a standard pattern might go for $40. Doppler knives have distinct phases, each with its own pricing tier. Even sticker placements matter — a skin with rare Katowice 2014 stickers in the right positions can multiply the base price several times over.
The Marketplace Ecosystem
Here’s where things get interesting from a tech perspective. Unlike most games where you buy skins from a single in-game store, CS2 has an entire ecosystem of competing marketplaces.
Steam Community Market is Valve’s own platform and the default option for most players. It’s integrated directly into the Steam client, making it convenient, but it comes with a 15% transaction fee and locks your earnings in Steam Wallet — you can’t cash out to real money.
It resulted in the creation of an extensive array of third-party marketplaces, which include websites like Skinport, DMarket, CSFloat, Buff163, and countless other options. These websites allow users to exchange skins for real money, using various means of payment, such as PayPal payments, bank transfers, and cryptocurrency transactions. The fee structures on these websites vary considerably, ranging from zero percent up to 10 percent and beyond.
This price fragmentation is exactly why analytics and comparison tools have become essential for anyone who takes CS2 trading seriously. Experienced traders routinely check CS2 prices across multiple platforms before making a move, because the price gap between the cheapest listing and the most expensive one for the same skin can easily be 15-30%.
Market Cap Tracking — Like Crypto, But For Skins
One of the more fascinating developments in the CS2 economy has been the adoption of financial tracking concepts borrowed from traditional and crypto markets.
The total CS2 market capitalization — the combined estimated value of every tradeable item in the ecosystem — is tracked in real time, much like how CoinMarketCap tracks cryptocurrency values.At the end of 2025, the peak market capitalization of CS2 was more than $6 billion; however, the market capitalization dropped by roughly 30% in a single move when Valve made an update (to be discussed later).
Such advanced monitoring is essential for the user to see whether the general market is expanding or contracting. If there is an increase in the market cap, then demand and investments are likely increasing; otherwise, a sharp drop may indicate a Valve update, season, or a major event in the global gaming economy.
The data-driven platform collects information from over 20 marketplaces and provides dashboards that contain trend analysis, volumes, and price movements that could have been taken directly from a professional stock trading platform. The economy of CS2 has reached such a degree of development that the very concept of “gaming” becomes irrelevant.
Trade-Up Contracts: The Economy’s Built-In Upgrade Path
Valve didn’t just build a marketplace — they built game mechanics directly into the economic system. However, the most crucial part is the Trade-Up Contracts where the user gets a skin from the next level collection using ten skins from the current level collection.
Even though this concept seems quite simple, it requires rather complex mathematical calculations. Namely, the output skin’s type is dependent on the input collections’ types, whereas its float is calculated according to the average float of all input skins scaled to the output collection’s range. Thus, an advanced player may affect the probability of getting a certain skin via inputs manipulation.
To explain, if seven skins belong to one collection while three skins are from another, the output skin will most probably originate from the first collection. If the first collection contains a $500 skin at the next tier and the second contains a $30 skin, you can engineer a heavily weighted gamble in your favor.
But here’s the catch — the math only works if you actually run the numbers. The inputs might cost $80 in total, but if the expected value of the output is only $60, you’re making a bad bet regardless of the potential upside. That’s why experienced traders simulate their contracts using a CS2 trade-up calculator before committing any skins. These tools predict every possible outcome with exact probabilities, float projections, and expected profit or loss.
The trade-up system was further shaken in October 2025 when Valve added the ability to trade up Covert skins into knives and gloves — something that was previously impossible. Players could suddenly turn five Covert skins worth roughly $5-10 each into knives that were previously selling for $1,000+. The result? Knife prices crashed overnight, the total market cap dropped by hundreds of millions, and the entire pricing hierarchy had to readjust.
The Tech Infrastructure Behind It All
All that lies beneath all these graphs and calculations is quite a bit of technology. Real-time data feeds, APIs, and aggregators pull pricing information from several different marketplaces simultaneously.
Automated trading, monitoring services, portfolio management tools, and other such applications are developed by third parties using the marketplace APIs. Some platforms offer their own developer APIs with endpoints for price recommendations, market analytics, and cross-platform price comparison — essentially creating the financial infrastructure layer that the CS2 economy needed to operate at scale.
Steam itself provides API access for inventory data, market listings, and transaction history, which third-party services use to power everything from inventory valuation tools to automated trading systems.
The sophistication has reached a point where the CS2 economy has its own version of Bloomberg terminals — dashboards that track market-wide trends, individual item price histories, trading volumes, liquidity scores, and even volatility metrics. Professional traders monitor these tools the same way a Wall Street analyst watches stock tickers.
Why It Matters Beyond Gaming
The CS2 skin economy isn’t just a curiosity — it’s a case study in how digital ownership, market dynamics, and community-driven value creation work at scale.
This is what some of the main points which can be derived from this are. Firstly, scarcity defines value in all instances. It has been illustrated in the CS2 skins case study, in which it is clear that it does not matter whether items are tangible or useful in order for them to have economic value.
Second, platform decisions have outsized economic impact. Valve’s single update in October 2025 erased over a billion dollars in virtual item value. No other company has that kind of direct influence over a player-driven economy of this scale.
And third, the line between gaming economies and financial markets is dissolving. When your hobby comes with real-time price tracking, market cap analytics, trade-up calculators, and cross-platform arbitrage opportunities, you’re not just playing a game anymore. You’re participating in a micro-economy that happens to live inside one.
Whether you’re a casual CS2 player who’s never sold a skin or a veteran trader running profit calculations on every drop, the scale and sophistication of what’s been built here is worth paying attention to. An $8 billion economy that runs on cosmetic pixels, community trust, and a few really good APIs — that’s the kind of thing you only find in gaming.
In addition to being a very popular first-person shooter game, Counter-Strike 2 is a great demonstration of the finest economic systems of games created so far. In particular, such an economic system is represented by virtual trading of items worth more than $8 billion. Indeed, one should bear in mind that this is not a typo – this figure really represents the cost of items worth $8 billion. It may be added that this amount is larger than GDP in many countries, despite not having any effect on the gameplay. So, how did some in-game items attain such a multi-billion dollar economy and what fuels it? We will explain.
How a Digital Skin Gets Its Price Tag
Every skin in CS2 has a set of properties that determine its value, and understanding them is the first step to making sense of this economy.
Rarity tier is the most obvious one. Skins are categorized from Consumer Grade (white, the most common) all the way up to Covert (red, the rarest non-knife items) and Contraband (the ultra-rare category with only one item — the M4A4 Howl). Knives and gloves sit in their own Extraordinary tier, which is part of why they command such premium prices.
Then there’s float value — a number between 0.00 and 1.00 that determines a skin’s visual condition. A float of 0.01 means the skin looks virtually brand new (Factory New), while 0.85 means it’s scratched up and Battle-Scarred. Two AK-47 Redlines might look similar at a glance, but a 0.01 float Factory New will sell for significantly more than a 0.15 Minimal Wear.
And finally, there are pattern-based factors. Certain skins like Case Hardened and Fade have pattern indexes that produce unique visual results. A Case Hardened AK-47 with a full blue gem pattern can sell for tens of thousands of dollars, while the same skin with a standard pattern might go for $40. Doppler knives have distinct phases, each with its own pricing tier. Even sticker placements matter — a skin with rare Katowice 2014 stickers in the right positions can multiply the base price several times over.
The Marketplace Ecosystem
Here’s where things get interesting from a tech perspective. Unlike most games where you buy skins from a single in-game store, CS2 has an entire ecosystem of competing marketplaces.
Steam Community Market is Valve’s own platform and the default option for most players. It’s integrated directly into the Steam client, making it convenient, but it comes with a 15% transaction fee and locks your earnings in Steam Wallet — you can’t cash out to real money.
It resulted in the creation of an extensive array of third-party marketplaces, which include websites like Skinport, DMarket, CSFloat, Buff163, and countless other options. These websites allow users to exchange skins for real money, using various means of payment, such as PayPal payments, bank transfers, and cryptocurrency transactions. The fee structures on these websites vary considerably, ranging from zero percent up to 10 percent and beyond.
This price fragmentation is exactly why analytics and comparison tools have become essential for anyone who takes CS2 trading seriously. Experienced traders routinely check CS2 prices across multiple platforms before making a move, because the price gap between the cheapest listing and the most expensive one for the same skin can easily be 15-30%.
Market Cap Tracking — Like Crypto, But For Skins
One of the more fascinating developments in the CS2 economy has been the adoption of financial tracking concepts borrowed from traditional and crypto markets.
The total CS2 market capitalization — the combined estimated value of every tradeable item in the ecosystem — is tracked in real time, much like how CoinMarketCap tracks cryptocurrency values.At the end of 2025, the peak market capitalization of CS2 was more than $6 billion; however, the market capitalization dropped by roughly 30% in a single move when Valve made an update (to be discussed later).
Such advanced monitoring is essential for the user to see whether the general market is expanding or contracting. If there is an increase in the market cap, then demand and investments are likely increasing; otherwise, a sharp drop may indicate a Valve update, season, or a major event in the global gaming economy.
The data-driven platform collects information from over 20 marketplaces and provides dashboards that contain trend analysis, volumes, and price movements that could have been taken directly from a professional stock trading platform. The economy of CS2 has reached such a degree of development that the very concept of “gaming” becomes irrelevant.
Trade-Up Contracts: The Economy’s Built-In Upgrade Path
Valve didn’t just build a marketplace — they built game mechanics directly into the economic system. However, the most crucial part is the Trade-Up Contracts where the user gets a skin from the next level collection using ten skins from the current level collection.
Even though this concept seems quite simple, it requires rather complex mathematical calculations. Namely, the output skin’s type is dependent on the input collections’ types, whereas its float is calculated according to the average float of all input skins scaled to the output collection’s range. Thus, an advanced player may affect the probability of getting a certain skin via inputs manipulation.
To explain, if seven skins belong to one collection while three skins are from another, the output skin will most probably originate from the first collection. If the first collection contains a $500 skin at the next tier and the second contains a $30 skin, you can engineer a heavily weighted gamble in your favor.
But here’s the catch — the math only works if you actually run the numbers. The inputs might cost $80 in total, but if the expected value of the output is only $60, you’re making a bad bet regardless of the potential upside. That’s why experienced traders simulate their contracts using a CS2 trade-up calculator before committing any skins. These tools predict every possible outcome with exact probabilities, float projections, and expected profit or loss.
The trade-up system was further shaken in October 2025 when Valve added the ability to trade up Covert skins into knives and gloves — something that was previously impossible. Players could suddenly turn five Covert skins worth roughly $5-10 each into knives that were previously selling for $1,000+. The result? Knife prices crashed overnight, the total market cap dropped by hundreds of millions, and the entire pricing hierarchy had to readjust.
The Tech Infrastructure Behind It All
All that lies beneath all these graphs and calculations is quite a bit of technology. Real-time data feeds, APIs, and aggregators pull pricing information from several different marketplaces simultaneously.
Automated trading, monitoring services, portfolio management tools, and other such applications are developed by third parties using the marketplace APIs. Some platforms offer their own developer APIs with endpoints for price recommendations, market analytics, and cross-platform price comparison — essentially creating the financial infrastructure layer that the CS2 economy needed to operate at scale.
Steam itself provides API access for inventory data, market listings, and transaction history, which third-party services use to power everything from inventory valuation tools to automated trading systems.
The sophistication has reached a point where the CS2 economy has its own version of Bloomberg terminals — dashboards that track market-wide trends, individual item price histories, trading volumes, liquidity scores, and even volatility metrics. Professional traders monitor these tools the same way a Wall Street analyst watches stock tickers.
Why It Matters Beyond Gaming
The CS2 skin economy isn’t just a curiosity — it’s a case study in how digital ownership, market dynamics, and community-driven value creation work at scale.
This is what some of the main points which can be derived from this are. Firstly, scarcity defines value in all instances. It has been illustrated in the CS2 skins case study, in which it is clear that it does not matter whether items are tangible or useful in order for them to have economic value.
Second, platform decisions have outsized economic impact. Valve’s single update in October 2025 erased over a billion dollars in virtual item value. No other company has that kind of direct influence over a player-driven economy of this scale.
And third, the line between gaming economies and financial markets is dissolving. When your hobby comes with real-time price tracking, market cap analytics, trade-up calculators, and cross-platform arbitrage opportunities, you’re not just playing a game anymore. You’re participating in a micro-economy that happens to live inside one.
Whether you’re a casual CS2 player who’s never sold a skin or a veteran trader running profit calculations on every drop, the scale and sophistication of what’s been built here is worth paying attention to. An $8 billion economy that runs on cosmetic pixels, community trust, and a few really good APIs — that’s the kind of thing you only find in gaming.
The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.”
Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:
Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.
In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.”
Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”
The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:
Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing.
The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits.
The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.”
Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:
Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.
In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.”
Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”
The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:
Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing.
The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits.
Then, in theory, it Daybreak patches them.
#Daybreak #OpenAIs #Answer #Anthropics #Project #Glasswing #ArrivedArtificial intelligence,Cybersecurity,OpenAI">‘Daybreak’: OpenAI’s Answer to Anthropic’s Project Glasswing Has Arrived
On Monday, OpenAI announced something called “Daybreak,” a project that CEO Sam Altman says is meant to “accelerate cyber defense and continuously secure software.“
OpenAI is launching Daybreak, our effort to accelerate cyber defense and continuously secure software.
AI is already good and about to get super good at cybersecurity; we’d like to start working with as many companies as possible now to help them continuously secure themselves.
The OpenAI blog post announcing Daybreak doesn’t mention the word “project” at all, perhaps to make readers slightly less apt to compare it to Anthropic’s Project Glasswing, but watch this: this sounds mighty similar to Anthropic’s Project Glasswing. Like Project Glasswing, it’s a program in which a frontier AI company seeks to partner with corporate and government entities to root out security vulnerabilities using OpenAI’s most advanced models in the hopes of “seeing risk earlier, acting sooner, and helping make software resilient by design.”
Glasswing rolled out last month alongside Anthropic’s announcement of its Claude Mythos Preview model, famously the model so capable—according to its creators at least—that it posed a danger to the world. As Anthropic’s system card for the model, explained:
Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.
In other words, because it’s “the most cyber-capable model” Anthropic had ever built, it needs to be locked away for now, unless you’re a VIP. Influential software developer Daniel Stenberg has called this an “amazingly successful marketing stunt for sure.”
Two days after that announcement, reports started materializing about a similar project at OpenAI. An anonymously sourced Axios story described it as “a product with advanced cybersecurity capabilities that it plans to release to a small set of partners.”
The Daybreak announcement is much more public-facing than that, and comes across as significantly less ominous and secretive than Project Glasswing. The top of the page has two buttons: “Request a vulnerability scan” and “Contact sales.” When you click, “Request a vulnerability scan” you get a brief and unchallenging form:
Altman said in his X post that OpenAI would “like to start working with as many companies as possible now,” and in fairness, that’s how the effort comes across. Compared to way Project Glasswing rolled out, with frightened governments scurrying around behind the scenes like agitated ants, it’s refreshing.
The announcement says Daybreak makes use of Codex Security, which was announced as a research preview back in March, to create a “threat model” of a given system that outlines its functions, who is trusted by the system, and what the vulnerabilities therefore are. With that as its context, it then digs into your actual codebase for the real world exploits.
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