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HTX Research Latest Report | Sonic: A Model for the New DeFi Paradigm

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SINGAPORE, April 28, 2025 /PRNewswire/ — As Layer 2 scaling solutions remain a focal point of industry discourse, Sonic presents a fundamental shift in blockchain architecture. HTX Research has announced the release of its latest report, “Sonic: A Model for the New DeFi Paradigm” The report dives into the details of the Sonic public chain.

Sonic’s Evolution: 2000+ TPS, 0.7s Confirmation, Near-Zero Fees

The Fantom Opera blockchain, initially recognized for its speed and throughput as a high-performance aDAG-based Layer 1 solution, encountered scalability limitations as its ecosystem expanded. Its traditional EVM architecture struggled with bloated state storage, slow node synchronization, and execution bottlenecks. To overcome these challenges without resorting to sharding or Layer 2 solutions, Fantom developed Sonic — a fundamental redesign engineered to deliver a significant performance leap.

Sonic Labs, a new team led by CEO Michael Kong, CTO Andre Cronje (founder of Yearn Finance), and Chief Research Officer Bernhard Scholz, dedicated two and a half years to the redesign of Fantom’s virtual machine, storage, and consensus. They built Sonic, a new, independent EVM-compatible chain capable of processing over 2,000 TPS, achieving 0.7-second finality, and executing transactions at a cost of $0.0001. It also improves storage efficiency by 90% and reduces node synchronization time from weeks to under two days.

Technical Innovations Driving Sonic’s Performance

Sonic’s enhanced performance is underpinned by three core technological advancements: 

SonicVM: A newly developed virtual machine fully compatible with the EVM, SonicVM optimizes computationally intensive operations like SHA3 hashing, pre-analyzes jump instructions, delivers significantly faster execution, and supports high throughput.

SonicDB: Achieving nearly 90% data compression, SonicDB uses a layered storage strategy that splits the blockchain state into two databases: LiveDB for the current global state and ArchiveDB for historical blocks and states. This reduces node requirements and enhances network resilience through greater decentralization.

Sonic Gateway: Functioning like an “L2-like” bridging solution to Ethereum, it uses a batch processing mechanism that strikes a balance between security and efficiency, enabling seamless two-way asset transfers and ecosystem access.

Stablecoin Ecosystem: Nested Yield and Resilient Growth

Defying market trends in 2025, Sonic’s on-chain Total Value Locked (TVL) surged by over 500%, with the total stablecoin supply surpassing $260 million. This growth is driven by sophisticated high-leverage yield mechanisms.

Silo v2 Loop Lending: Use staked S tokens to borrow stablecoins, achieving up to 20x exposure to capture combined incentives alongside stable yield spreads.Euler + Rings Protocol Combo: Deposit USDC to mint scUSD, then use leverage to potentially achieve up to 10x yield, along with Sonic points and protocol rewards.Shadow DEX Liquidity Provision for Rewards: By facilitating trading activity, particularly with the S/stS pair on Shadow, users can earn up to 169% APY and a share of trading fees.

Looking ahead, the ecosystem will incorporate Real World Asset (RWA) yields and off-chain payment solutions to create a sustainable and widely used stablecoin ecosystem backed by compliant assets and real-world applications.

Conclusion: Sonic – Leading the Charge in DeFi 2.0

Sonic’s high performance, nested yields, and accessibility position it for rapid growth, with the potential to exceed $2B TVL and a multi-billion $S token market cap within a year. More importantly, Sonic is championing an “efficiency revolution” in blockchain design—prioritizing performance and capital efficiency to attract liquidity.

The report identifies technical challenges, including the adaptive AMM’s reliance on external oracles, which introduces potential vulnerabilities. Furthermore, the inherent risks of high-leverage strategies in volatile markets necessitate the use of hedging instruments, such as short perpetual futures, to mitigate potential liquidations.

From a broader view, Sonic is well-positioned to lead the expected 2025 DeFi resurgence. Its thriving stablecoin ecosystem boosts the value of both the $S token and the network. Even in a bear market, Sonic demonstrates the potential for DeFi to establish resilient “yield havens” through innovation and performance. With its nested yields, developer-focused incentives, and efficient infrastructure, Sonic provides a model for the industry. The integration of RWAs and payment tools could place Sonic as a critical bridge between on-chain yields and real-world utility, driving DeFi toward mass adoption

For full report, please visit: https://square.htx.com/wp-content/uploads/2025/04/HTX-Research-Latest-Report-1-1.pdf

About HTX Research

HTX Research is the dedicated research arm of HTX Group, responsible for conducting in-depth analyses, producing comprehensive reports, and delivering expert evaluations across a broad spectrum of topics, including cryptocurrency, blockchain technology, and emerging market trends.

 

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Chef Robotics Physical AI Models Can Now Automate Baked Goods Packing

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SAN FRANCISCO, April 29, 2026 /PRNewswire/ — Chef Robotics, a leader in physical AI for the food industry, today announced that Chef robots can now automate tray assembly for baked goods packing. The application places baked products, such as burger buns, chocolate chip cookies, biscotti, butter cookies, biscuits, fortune cookies, granola bars, rusks, and shortbreads into trays and packaging containers before sealing.

Watch Chef robots in action.

Baked goods packing has historically been difficult to automate for high-mix production. Each item behaves differently on the production line—a granola bar compresses under the wrong grip, while a biscotti or rusk can crack if placed at the wrong angle. Surface textures range from glazed and smooth to crumbly and irregular, and strict presentation requirements leave little room for error. This variability has made it challenging for automation systems to reliably handle baked goods at production speeds, leaving food manufacturers dependent on manual labor and traditional bakery equipment.

To address this, Chef built its baked goods packing application on its existing piece-picking capability, which uses Chef’s AI-powered computer vision and physical AI models trained across diverse real-world production environments. This allows Chef robots to assess each item’s position, shape, and orientation in real time and determine how to pick the items from the pan and place them quickly and precisely without damaging them.

The baked goods packing application supports four distinct placement capabilities.

First, Chef’s vision system detects the angle at which each item sits in the pan and reorients it after picking, placing it on the tray at the exact angle required, regardless of its original position, enabling retail-ready presentation for SKUs that require precise angular placement.

Second, Chef robots can place multiple baked goods into the same packaging container in a single automated pass, completing full tray assembly without manual intervention.

Third, for packaging containers with multiple small compartments, Chef robots can precisely place items into each designated section, including multiple items in the same compartment, using Chef’s AI vision model to detect compartment positions and orientations in real time.

Fourth, Chef’s vision system identifies the exact center of each tray and places every item at a predefined offset from that center, ensuring a uniform, consistent arrangement across every pack regardless of how trays arrive on the conveyor.

For food manufacturers evaluating bakery systems and baked goods packaging automation, the application offers higher throughput, reduced labor dependency, and consistent presentation across shifts. The capability runs on Chef’s existing robotic hardware and software, allowing manufacturers to deploy it without requiring any changes to their production lines.

Chef’s baked goods packing application is available in the U.S., Canada, Germany, and the UK and is included as part of Chef’s robotics-as-a-service (RaaS) pricing model.

About Chef Robotics
Chef is the first company to have commercialized a scalable AI-driven food robotics solution. With over 104 million servings made in production, Chef leverages ChefOS, an AI platform for food manipulation, to offer a Robotics-as-a-Service solution that helps industry-leading food companies increase production volume and meet demand. Headquartered in San Francisco, CA, Chef aims to empower humans to do what humans do best by accelerating the advent of intelligent machines. Visit https://chefrobotics.ai to learn more.

View original content:https://www.prnewswire.com/news-releases/chef-robotics-physical-ai-models-can-now-automate-baked-goods-packing-302756923.html

SOURCE Chef Robotics

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Chef Robotics Physical AI Models Can Now Automate Baked Goods Packing

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SAN FRANCISCO, April 29, 2026 /PRNewswire/ — Chef Robotics, a leader in physical AI for the food industry, today announced that Chef robots can now automate tray assembly for baked goods packing. The application places baked products, such as burger buns, chocolate chip cookies, biscotti, butter cookies, biscuits, fortune cookies, granola bars, rusks, and shortbreads into trays and packaging containers before sealing.

Watch Chef robots in action.

Baked goods packing has historically been difficult to automate for high-mix production. Each item behaves differently on the production line—a granola bar compresses under the wrong grip, while a biscotti or rusk can crack if placed at the wrong angle. Surface textures range from glazed and smooth to crumbly and irregular, and strict presentation requirements leave little room for error. This variability has made it challenging for automation systems to reliably handle baked goods at production speeds, leaving food manufacturers dependent on manual labor and traditional bakery equipment.

To address this, Chef built its baked goods packing application on its existing piece-picking capability, which uses Chef’s AI-powered computer vision and physical AI models trained across diverse real-world production environments. This allows Chef robots to assess each item’s position, shape, and orientation in real time and determine how to pick the items from the pan and place them quickly and precisely without damaging them.

The baked goods packing application supports four distinct placement capabilities.

First, Chef’s vision system detects the angle at which each item sits in the pan and reorients it after picking, placing it on the tray at the exact angle required, regardless of its original position, enabling retail-ready presentation for SKUs that require precise angular placement.

Second, Chef robots can place multiple baked goods into the same packaging container in a single automated pass, completing full tray assembly without manual intervention.

Third, for packaging containers with multiple small compartments, Chef robots can precisely place items into each designated section, including multiple items in the same compartment, using Chef’s AI vision model to detect compartment positions and orientations in real time.

Fourth, Chef’s vision system identifies the exact center of each tray and places every item at a predefined offset from that center, ensuring a uniform, consistent arrangement across every pack regardless of how trays arrive on the conveyor.

For food manufacturers evaluating bakery systems and baked goods packaging automation, the application offers higher throughput, reduced labor dependency, and consistent presentation across shifts. The capability runs on Chef’s existing robotic hardware and software, allowing manufacturers to deploy it without requiring any changes to their production lines.

Chef’s baked goods packing application is available in the U.S., Canada, Germany, and the UK and is included as part of Chef’s robotics-as-a-service (RaaS) pricing model.

About Chef Robotics
Chef is the first company to have commercialized a scalable AI-driven food robotics solution. With over 104 million servings made in production, Chef leverages ChefOS, an AI platform for food manipulation, to offer a Robotics-as-a-Service solution that helps industry-leading food companies increase production volume and meet demand. Headquartered in San Francisco, CA, Chef aims to empower humans to do what humans do best by accelerating the advent of intelligent machines. Visit https://chefrobotics.ai to learn more.

View original content:https://www.prnewswire.com/news-releases/chef-robotics-physical-ai-models-can-now-automate-baked-goods-packing-302756923.html

SOURCE Chef Robotics

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Air Products to Expand Industrial Gas Supply for Samsung Electronics’ Next-Generation Semiconductor Fab in South Korea

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New investment underscores the company’s long-term commitment to Korea and its leading role in the global semiconductor industry 

LEHIGH VALLEY, Pa., April 29, 2026 /PRNewswire/ — Air Products (NYSE:APD), a world-leading industrial gases company and serving Samsung globally, today announced it has been selected by Samsung to supply industrial gases for its new advanced semiconductor fab in Pyeongtaek, Gyeonggi Province, South Korea.

Under the agreement, Air Products will build, own and operate multiple state-of-the-art production facilities and a bulk specialty gas supply system to supply nitrogen, oxygen, argon, and hydrogen for Samsung’s new semiconductor fab. The new facilities are expected to come onstream in multiple phases from 2028 through 2030.

Air Products has a long track record of executing multiple phase expansions in Pyeongtaek to support Samsung’s growing manufacturing needs. This latest project represents Air Products’ largest investment to date in the semiconductor industry and will establish Pyeongtaek as the company’s single largest operations site globally supporting the electronics industry. 

“Air Products is honored to be selected once again by Samsung and to have their continued confidence as a trusted partner supporting their strategic growth plans,” said SR Kim, President, Air Products Korea. “This significant investment reinforces Air Products’ role as a leading global supplier to the semiconductor industry and underscores our long-standing commitment to supporting our strategic customers with safety, reliability, efficiency and excellent service.”

Air Products has served the global electronics industry for more than 40 years, supplying industrial gases safely and reliably to many of the world’s leading technology companies. The company has operated in Korea for more than 50 years and has established a strong position in electronics and manufacturing sectors.

About Air Products

Air Products (NYSE: APD) is a world-leading industrial gases company in operation for over 85 years focused on serving energy, environmental, and emerging markets and generating a cleaner future. The Company supplies essential industrial gases, related equipment and applications expertise to customers in dozens of industries, including refining, chemicals, metals, electronics, manufacturing, medical and food. As the leading global supplier of hydrogen, Air Products also develops, engineers, builds, owns and operates some of the world’s largest clean hydrogen projects, supporting the transition to low- and zero-carbon energy in the industrial and heavy-duty transportation sectors. Through its sale of equipment businesses, the Company also provides turbomachinery, membrane systems and cryogenic containers globally.

Air Products had fiscal 2025 sales of $12 billion from operations in approximately 50 countries. For more information, visit airproducts.com or follow us on LinkedInXFacebook or Instagram.

This release contains “forward-looking statements” within the safe harbor provisions of the Private Securities Litigation Reform Act of 1995. These forward-looking statements are based on management’s expectations and assumptions as of the date of this release and are not guarantees of future performance. While forward-looking statements are made in good faith and based on assumptions, expectations and projections that management believes are reasonable based on currently available information, actual performance and financial results may differ materially from projections and estimates expressed in the forward-looking statements because of many factors, including the risk factors described in our Annual Report on Form 10-K for the fiscal year ended September 30, 2025 and other factors disclosed in our filings with the Securities and Exchange Commission. Except as required by law, we disclaim any obligation or undertaking to update or revise any forward-looking statements contained herein to reflect any change in the assumptions, beliefs or expectations or any change in events, conditions or circumstances upon which any such forward-looking statements are based.

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