KAIST AI Will Use Theta EdgeCloud to Accelerate AI Model Training as First Academia Customer

THETAPublished on 2024-07-18Last updated on 2024-07-22

KAIST AI Will Use Theta EdgeCloud to Accelerate AI Model Training as First Academia Customer

Theta Labs
Theta Network
Published in
3 min read2 days ago

Theta has already entered a new era in 2024 with the release of EdgeCloud in May. Now, we’re thrilled to announce a new partnership between Theta Labs and KAIST AI, marking a significant convergence of our EdgeCloud and cutting-edge academic research. This multi-year agreement will see KAIST AI, one of the world’s leading AI research institutions, utilizing Theta EdgeCloud to power their cutting-edge computer vision and natural language processing projects.

KAIST, often referred to as the “MIT of Korea,” has consistently ranked among the top institutions globally for machine learning research. Their decision to adopt Theta EdgeCloud speaks volumes about the platform’s real-world capabilities and potential advance AI infrastructure in a decentralized way.

At the heart of this collaboration is Professor Jaegul Choo, an Endowed Chair Professor at KAIST, whose team will be leveraging Theta EdgeCloud for their innovative work. One of their recent breakthroughs, StableVITON, showcases the power of AI in the fashion industry. This fine-tuned stable diffusion model can seamlessly superimpose clothing onto images of individuals, preserving their features and pose with remarkable accuracy.

As you may know, what sets Theta EdgeCloud apart is its unique hybrid architecture. As Professor Choo notes, “EdgeCloud is the only hybrid platform in the market where a particular AI job can be optimized for price, performance and depending on requirements routed to either high performing A100s/H100s cloud GPUs or to NVIDIA 3090s/4090s desktop GPUs as part of Theta’s distributed edge network.” This flexibility allows researchers to tailor their computing resources to the specific needs of each project, maximizing efficiency and cost-effectiveness.

The partnership doesn’t stop at StableVITON. KAIST AI and Theta Labs are already planning their next collaborative milestone: expanding the model to include new wearables, including more complex objects like hats. This GPU-intensive task will harness the full power of Theta EdgeCloud’s cluster of A100s and H100s, pushing the boundaries of what’s possible in AI-driven fashion technology.

For Theta, this partnership represents a major step into the academic research sector. Our EdgeCloud platform, powered by over 30,000 distributed edge nodes and cloud partners like Google Cloud and Amazon Web Services, offers over 80 PetaFLOPS of always available distributed GPU compute power. This makes it an ideal solution for the complex, resource-intensive tasks that cutting-edge AI research demands.

The implications of this research extend far beyond academia. As Mitch Liu, co-founder and CEO of Theta Labs, points out, “This unlocks a market opportunity of over 30,000 universities worldwide with multiple AI research groups and labs, spending billions of dollars every year for GPU-intensive AI tasks.”

You can try the Virtual Try-on Generative AI tool here, have fun!

Trending Cryptos

Related Reads

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

In mid-June, three seemingly independent industry events—the compliance-driven throttling of Fable 5, the open-sourcing of GLM-5.2, and the leaked release timeline for GPT-5.6—are pushing the global AI industry toward a watershed moment. These shifts signal a fundamental restructuring of the industry's underlying logic. First, **"usability" has substantially overtaken "advanced capabilities"** as the primary weight, pushing the global large language model (LLM) supply chain into a "dual-track" phase of controlled closed-source and local open-source coexistence. Second, **the competitive moats of closed-source giants are shifting**. Their technical focus is moving from "language intelligence" toward "spatial intelligence (world models)"—a domain heavily reliant on computing power. Third, faced with常态化 transnational compliance risks, **a "model-agnostic" decoupled design has become a survival necessity for application-layer developers to maintain business continuity.** The article details how Anthropic's Fable 5, despite its advanced engineering feats, was restricted for non-U.S. citizens within 72 hours of launch, highlighting how geopolitical compliance can instantly limit even the most advanced models. In response, the open-source camp, exemplified by Zhipu AI's MIT-licensed GLM-5.2, is gaining market share by offering stable performance improvements and significant cost advantages (up to 70% savings for enterprises), while achieving full adaptation with domestic semiconductor platforms. Meanwhile, closed-source leaders like OpenAI are pivoting. The anticipated GPT-5.6 reportedly shifts focus from language to spatial intelligence and world models, aiming to rebuild a generational gap in areas like 3D understanding, simulation, and industrial design that demand immense compute. The core conclusion is that the LLM supply chain's logic has changed. Enterprises must now evaluate infrastructure based on a composite of technical performance and policy compliance. For developers, complete reliance on a single closed-source API poses unacceptable risk. Implementing a truly model-agnostic architecture—enabling swift switches to compliant, locally deployable open-source alternatives—is no longer just good practice but a fundamental baseline for business continuity.

marsbit2h ago

GPT-5.6 Countdown: Abandon the Illusion of a Single API, Computational Iteration Can't Outpace a Single Page of Compliance

marsbit2h ago

Is the 'Token Subsidy War' Among AI Giants Almost Over?

The article discusses the ongoing "token subsidy war" among AI giants like OpenAI and Anthropic, questioning whether it's nearing its end. It reveals that current AI subscription prices are heavily subsidized, with some plans offering tokens at up to 70 times the actual cost to attract and retain heavy users, especially developers and enterprises. This strategy mirrors past internet-era subsidy battles, but with a key difference: AI tokens lack "lock-in" effects. Unlike ride-hailing or food delivery apps, users can easily switch between AI providers as APIs become standardized, making it difficult for companies to raise prices post-subsidy. The piece highlights a structural asymmetry in the competition. Giants like Google, with massive advertising revenue, can afford to subsidize tokens indefinitely, akin to using "tokens as a weapon." In contrast, venture-backed companies like OpenAI and Anthropic face pressure to become profitable, especially as they approach IPO. The article cites Google Ventures founder Bill Maris, who suggests Google could slash token prices by 80%, putting immense pressure on competitors. Two potential endgames are presented: the "internet service" model (subsidize, monopolize, then raise prices) and the "utility" model (tokens become a standardized, low-margin commodity like electricity). Given the low switching costs, the latter seems more likely. The competition may not have a single winner but could instead accelerate AI's evolution into a foundational, infrastructure-level technology, akin to a public utility. For now, users continue to benefit from heavily subsidized token costs.

marsbit2h ago

Is the 'Token Subsidy War' Among AI Giants Almost Over?

marsbit2h ago

Beyond the Stadium: The Profitable Games Surrounding the World Cup

"Beyond the Pitch: The Profit Game Around the World Cup" The FIFA World Cup transcends being a sporting spectacle, evolving into a massive global arena for speculation and profit-seeking. The 2026 tournament has amplified this dynamic, creating a multi-layered ecosystem of financial opportunism alongside the football. **Prediction markets** have surged into the mainstream. Platforms like Polymarket and Kalshi saw trading volumes for World Cup contracts soar, attracting new users with their financial trading model and high-profile, chain-based wealth stories that overshadow traditional sports betting in terms of growth and narrative. However, **traditional sportsbooks** remain the dominant force, leveraging established user habits, legal markets, and comprehensive product offerings to handle the vast majority of speculative wagers, with projections suggesting record-breaking betting volumes. Capital markets also react. **"Concept stocks"** in countries like South Korea and Japan experience volatile price swings based on team performance and anticipated fan spending on items like chicken, beer, and viewing parties, effectively becoming a stock market reflecting fan sentiment. The **ticket resale market** has become a sophisticated arena for arbitrage. Prices fluctuate wildly based on team draws and star power, with sellers sometimes listing tickets they don't yet own in a practice akin to short-selling, while FIFA's own "Right to Buy" tokens add another layer of speculative trading. **Collectibles and merchandise** offer another avenue. Panini sticker albums, with their inherent scarcity and nostalgic value, can become high-value collectibles. Limited-edition or locally themed jerseys command significant premiums on secondary markets, and even counterfeit vendors profit from fans' desire for affordable match-day identity. The **cryptocurrency** space has seen a frenzy of speculative, unauthorized World Cup-themed meme coins on chains like Solana. These tokens, often exploiting team names and player imagery, experience extreme pump-and-dump cycles, creating stories of massive gains for a few early entrants and steep losses for many others. Finally, an entire industry thrives on **providing information and tools** to other speculators. Developers create platforms like SeatSidekick to track ticket inventory and prices, while paid Telegram groups and subscriptions sell betting tips and predictions, monetizing the widespread desire for an informational edge. In essence, the World Cup has become a compressed, global laboratory for speculation. While the games determine champions on the field, a parallel, complex network of financial transactions—spanning prediction contracts, bets, stocks, tickets, collectibles, crypto, and information services—settles its own scores in the global market.

marsbit3h ago

Beyond the Stadium: The Profitable Games Surrounding the World Cup

marsbit3h ago

Trading

Spot
Futures

Hot Articles

How to Buy THETA

Welcome to HTX.com! We've made purchasing Theta (THETA) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Theta (THETA) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Theta (THETA)After purchasing your Theta (THETA), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Theta (THETA)Easily trade Theta (THETA) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

4.6k Total ViewsPublished 2024.03.29Updated 2026.06.02

How to Buy THETA

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of THETA (THETA) are presented below.

活动图片