Published: August 27, 2025 at 3:20 am Updated: August 27, 2025 at 3:20 am
by Ana
Edited and fact-checked:
August 27, 2025 at 3:20 am
To improve your local-language experience, sometimes we employ an auto-translation plugin. Please note auto-translation may not be accurate, so read original article for precise information.
In Brief
CoinList has launched Alpha, a private investment portal, debuting with the STSS PIPE supporting Sharps Technology’s shift to a Solana-focused treasury strategy under CIO Alice Zhang.
Cryptocurrency exchange and token launch platform, CoinList introduced CoinList Alpha, a private portal designed to provide accredited investors with access to carefully selected private offerings, ranging from early-stage seed rounds to private placements in treasury companies.
Traditionally, such private placement opportunities were available only to venture capital firms and large institutions, but Alpha broadens this access to a wider network of accredited investors, enabling participation in startup deals at various stages, including pre-seed, pre-token generation events, and pre-public rounds.
The CoinList Alpha portal serves as a bridge for both startups and established companies, helping them connect with a broader pool of accredited angel investors beyond the typical base of institutional players and VCs. The platform has a history of connecting ambitious projects with capital and communities, facilitating over $1.2 billion in funding and serving as a launchpad for well-known cryptocurrency ventures such as Solana, Filecoin, and Near.
With the introduction of Alpha, CoinList expands its role into private market deals, operating at the intersection of cryptocurrency and traditional capital markets.
CoinList Launches First Alpha Deal With STSS PIPE, Supporting Sharps Technology’s Shift To Solana Treasury Strategy
For its first transaction under the new initiative, CoinList provided eligible customers with access to the STSS PIPE, which marked Sharps Technology’s transition toward becoming a Solana-focused treasury company under the leadership of its newly appointed Chief Investment Officer, Alice Zhang.
Earlier in the week, Sharps Technology, Inc. confirmed the pricing of a private placement designed to fund its adoption of a digital asset treasury strategy centered on Solana (SOL) as its principal holding. Solana is currently regarded as the fastest and most widely used public blockchain, handling more transactions and generating greater on-chain fee revenue than the combined total of all other blockchains.
The structure of the offering involves a private investment in public equity (PIPE) valued at over $400 million, consisting of common stock (and/or pre-funded warrants for common stock) together with stapled warrants to purchase additional shares. The units are priced at $6.50 each, with the stapled warrants carrying a three-year term and an exercise price of $9.75, equivalent to 150 percent of the initial unit price. The PIPE transaction is anticipated to close on or around August 28th, 2025, subject to the fulfillment of standard closing requirements.
Disclaimer
In line with the Trust Project guidelines, please note that the information provided on this page is not intended to be and should not be interpreted as legal, tax, investment, financial, or any other form of advice. It is important to only invest what you can afford to lose and to seek independent financial advice if you have any doubts. For further information, we suggest referring to the terms and conditions as well as the help and support pages provided by the issuer or advertiser. MetaversePost is committed to accurate, unbiased reporting, but market conditions are subject to change without notice.
About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
More articles
Alisa Davidson
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
For years, I’ve relied entirely on a complex web of keyboard shortcuts to muscle my way through Premiere Pro and Lightroom. While fast, it’s rarely intuitive. When Logitech acquired Loupedeck and subsequently announced the MX Creative Console, it caught my attention. Promising a streamlined, modular approach to creative workflows at a relatively accessible price point, it seemed like the perfect bridge between a standard keyboard and a massively expensive, specialized editing suite. I integrated this two-piece system into my daily production setup to see if it could genuinely speed up my editing or if it was just another piece of desk clutter.
Pros & Cons
✅ Modular Freedom: The split design allows you to place the dial unit on one side of your keyboard and the LCD keypad on the other, maximizing ergonomics.✅ Deep Adobe Integration: Works seamlessly right out of the box with Premiere Pro, Photoshop, Lightroom, and After Effects through native plugins.✅ Premium Tactile Feel: The solid aluminum dial and smooth roller provide excellent, granular control for timeline scrubbing and color grading.❌ Battery Operated Dial: The wireless Dialpad runs on two AAA batteries rather than utilizing a modern, built-in rechargeable lithium-ion battery.❌ Wired Keypad Requirement: The Keypad module with the LCD screens requires a constant wired USB-C connection, which adds a cable to your desk.❌ Software Learning Curve: While setting up basic tools is easy, building complex, multi-layered macros in Logi Options+ requires patience.
FeatureDetailsModulesTwo-piece system (Keypad and Dialpad)Keypad Features9 Customizable LCD Display Keys, 2 Pagination ButtonsDialpad FeaturesAluminum Dial, Roller, 4 Tactile ButtonsConnectivity (Keypad)Wired via USB-CConnectivity (Dialpad)Wireless via Bluetooth Low EnergyPower (Dialpad)2x AAA Batteries (Up to 18 months battery life)SoftwareLogi Options+ (Windows 10/11, macOS 13+)
My Experience
Unboxing the MX Creative Console, the Logitech design language is immediately apparent. It perfectly matches the aesthetic of their MX Master mouse and MX Keys keyboards. The decision to split the console into two separate modules—a wireless Dialpad and a wired LCD Keypad—is a stroke of genius. Unlike monolithic editing boards that force your hands into specific, often cramped positions, I could place the Dialpad on the left side of my keyboard to handle timeline scrubbing with my left hand, while keeping my right hand free for mouse work and tapping the LCD keypad. This ergonomic freedom completely eliminated the shoulder strain I usually feel after a long editing session.
The physical hardware is a joy to interact with. The oversized aluminum dial on the wireless module has a satisfying weight to it. When color grading in Lightroom, assigning the dial to exposure or contrast adjustments felt significantly more precise than dragging sliders with a mouse. The roller wheel, situated just above the dial, became my go-to for adjusting brush sizes in Photoshop. Meanwhile, the wired Keypad features nine incredibly bright and sharp LCD display keys. Having my most-used tools dynamically update with visual icons based on whichever app I currently have open is a massive time-saver, completely negating the need to memorize obscure key combinations.
The software backbone, Logi Options+, clearly benefits from Logitech’s acquisition of Loupedeck. The native integration with the Adobe Creative Cloud suite is incredibly deep. Without any complicated setup, the console knew exactly what to do the second I opened Premiere Pro. However, stepping outside the Adobe ecosystem requires a bit more effort. While you can map standard keyboard shortcuts to the console for applications like DaVinci Resolve or Final Cut Pro, you lack the deep, API-level integration found in the Adobe suite. Setting up custom profiles for these apps is totally doable, but it requires spending some serious time in the software.
There are a couple of hardware quirks that irked me. First, while I appreciate that the Dialpad is wireless, the reliance on AAA batteries instead of USB-C recharging feels a bit dated for a modern, premium device. Second, because the LCD Keypad requires substantial power to run its screens, it must remain tethered via USB-C, meaning your desk will never be entirely cable-free. Despite these minor complaints, the MX Creative Console has fundamentally smoothed out my daily workflow. It brings the high-end tactile experience of professional studio equipment to a surprisingly accessible price point.
Who is this for? / Alternatives
The Logitech MX Creative Console is designed primarily for photo and video editors, digital artists, and power users deeply entrenched in the Adobe Creative Cloud ecosystem. If you just need simple macro buttons for streaming, an Elgato Stream Deck might be more straightforward. If you want a more compact, all-in-one tactile controller, the TourBox Elite is a formidable competitor, though it lacks the dynamic visual feedback of the MX’s LCD keys.
Quick FAQ
Does the console only work with Adobe software?Not at all. While the native integrations are built for Adobe, you can map standard keyboard shortcuts and multi-step macros to the device for absolutely any application using the Logi Options+ software.
Can I use both modules wirelessly?No. The Keypad with the LCD screens requires a continuous wired USB-C connection for both data and power, while the Dialpad operates entirely wirelessly via Bluetooth.
Are the screens on the keypad customizable?Yes, highly customizable. You can utilize Logitech’s expansive built-in library of icons or upload your own custom graphics for complete personalization of your workspace.
Logitech MX Creative Console Review
Ergonomics & Design – 9.5/10
Software Integration – 8.5/10
Customizability – 9.0/10
Value for Money – 8.0/10
“A brilliantly modular, highly tactile control surface that drastically accelerates creative workflows, especially if you live inside the Adobe ecosystem.”
Published: March 21, 2025 at 11:14 am Updated: March 21, 2025 at 11:14 am
by Ana
Edited and fact-checked:
March 21, 2025 at 11:14 am
To improve your local-language experience, sometimes we employ an auto-translation plugin. Please note auto-translation may not be accurate, so read original article for precise information.
In Brief
NVIDIA has unveiled Newton, an open-source and extensible physics engine developed in collaboration with Google DeepMind and Disney Research, aimed at enhancing robot learning and development.
Technology company NVIDIA has unveiled Newton, an open-source and extensible physics engine developed in collaboration with Google DeepMind and Disney Research, aimed at enhancing robot learning and development.
Based on NVIDIA Warp, which allows robots to learn complex tasks with improved accuracy, Newton is designed to work seamlessly with learning frameworks like MuJoCo Playground and NVIDIA Isaac Lab, an open-source platform for unified robot learning.
Physical AI models allow robots to autonomously understand, analyze, reason, and engage with their surroundings. The advancement of robotics heavily relies on accelerated computing and simulations to develop the next generation of robotic systems.
Physics is essential in robotic simulation, as it forms the basis for creating accurate virtual models that represent how robots behave and interact in real-world environments. Through these simulators, researchers and engineers are able to train, design, test, and validate control algorithms and prototypes in a secure, efficient, and cost-effective way.
Newton is designed to support the entire robotics community, allowing roboticists to freely use, distribute, and contribute to its development with research. Built on NVIDIA Warp, a CUDA-X acceleration library, it offers developers an efficient way to create GPU-accelerated, kernel-based programs for simulation, AI, robotics, and machine learning (ML). This framework provides high-performance capabilities for running physics-based simulations, utilizing the parallel processing power of NVIDIA GPUs.
A notable feature of Newton is its compatibility with Multi-Joint dynamics with Contact (MuJoCo), an established open-source physics engine used in robotics research for modeling complex dynamics and contact-rich environments. This compatibility allows developers to reuse existing models and code, reducing the time and resources required to adapt applications for different physics engines.
Additionally, Google DeepMind has introduced MuJoCo-Warp, an open-source robotics simulator accelerated by NVIDIA Warp, which delivers performance improvements, achieving more than a 70x speedup for humanoid simulations and a 100x speedup for in-hand manipulation tasks. MuJoCo-Warp will be integrated as a primary physics engine in Newton, offering developers enhanced performance and flexibility for their robotics applications.
More Key Features Of Newton: Differentiable Physics, Extensibility, And OpenUSD Integration
Furthermore, its ability to propagate gradients through simulation introduces new opportunities for robotics simulation and learning. Differentiable simulators are capable of generating forward-mode results while also calculating reverse-mode gradients of simulation outcomes, which can then be used for back-propagation to optimize system parameters.
As the field of robotics evolves, so does the complexity and variety of scenarios that need to be simulated. Newton is designed to be highly adaptable, supporting rich multiphysics simulations where robots interact with a range of materials, including food, cloth, and other deformable objects. This flexibility is enabled by custom solvers, integrators, and numerical methods. Newton also supports coupling different types of solvers, as demonstrated in the integration of a material point method (MPM) solver with rigid body dynamics for simulating interactions with sand.
Moreover, Newton leverages the OpenUSD framework, which offers a versatile data model and composition engine that aggregates the necessary data to describe robots and their environments. Custom solvers and runtimes can be specialized for specific robotic capabilities and environments. Furthermore, alongside Disney Research, Google DeepMind, Intrinsic, and NVIDIA, Newton is helping to define an OpenUSD asset structure for robotics. This structure aims to standardize robotic workflows by adopting best practices within OpenUSD, creating a unified data pipeline that provides a common language for all data sources in robotics.
Disclaimer
In line with the Trust Project guidelines, please note that the information provided on this page is not intended to be and should not be interpreted as legal, tax, investment, financial, or any other form of advice. It is important to only invest what you can afford to lose and to seek independent financial advice if you have any doubts. For further information, we suggest referring to the terms and conditions as well as the help and support pages provided by the issuer or advertiser. MetaversePost is committed to accurate, unbiased reporting, but market conditions are subject to change without notice.
About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
More articles
Alisa Davidson
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
Published: February 20, 2026 at 8:40 am Updated: February 20, 2026 at 7:42 am
To improve your local-language experience, sometimes we employ an auto-translation plugin. Please note auto-translation may not be accurate, so read original article for precise information.
In Brief
Crypto sentiment entering 2026 sits in deep Extreme Fear, with markets showing sustained risk aversion and no clear shift toward a Greed phase until broader macro, liquidity, and confidence conditions materially improve.
Cryptocurrency markets started 2026 in an extremely pessimistic mode. The sentiment measures were down to the Extreme Fear category, which indicates market bottoms and not a manic run-up. The next question now for analysts, traders, and long-term investors is when the next zone of Greed may come, indicating a high bullishness and overall confidence in the market. To view this timeline, it is necessary to take a look at not only up-to-date sentiment data but also the history of crypto cycles.
By February 18, 2026, the Crypto Fear & Greed Index, one of the most common indicators of the state of market psychology, is only at 9 out of 100, which is evidently in the realm of Extreme Fear. Such a low reading suggests that traders and investors, as well as even institutional traders, are suffering widespread risk aversion and extreme caution. A score below 20 has traditionally been associated with protracted sell-offs, volatile trading, and the wave of capitulation.
Prior to markets being in a Greed zone, which is generally characterized by a reading of above 60, various factors about price momentum, investor confidence, macroeconomic stability, and liquidity will have to change considerably. Nevertheless, researching the evidence of sentiment indices, technical indicators, and crypto-cycle patterns, scholars and market commentators are starting to map when a movement to the greed sentiment may plausibly happen.
Current Crypto Sentiment: Under the Shadow of Extreme Fear
The mood image is not positive at the moment. The Crypto Fear & Greed Index has recorded several times in the single-digit figures, even a record low of 5 in early February 2026, indicating the deepest reluctance in the market.
To measure the overall investor mood, the measurement consolidates statistics from various sources, such as price volatility, market momentum, social media activity, volume of trade, the dominance of bitcoins in the market, and Google search results. A score under 20 is usually an Extreme Fear, which means that a significant portion of the market members are abandoning the risk and minimizing the exposure to digital assets.
This fear has been the order of the day and has accompanied significant price contractions. An example is the case of Bitcoin that retested the support at the levels of $60,000–$70,000.
This level has been used as a psychological aspect over the last several months. These extended periods of bearishness are usually indicators of either an extension of the negative price movement or a time during which the markets absorb weak holders and then major, sustained upturns.
This is because some commentators believe that long durations of intense fear, especially where sentiment measures are below historic levels, may lead to a change of heart in the market psychology. In mid-2022, another trough in sentiment led to one of the largest bull runs in late 2023 into 2024.
Nonetheless, the interval between the greatest fear and the start of the greedy interval fluctuated significantly throughout the cycles, indicating that although a bad mood can be a precursor to a subsequent recovery, the process relies on numerous macro market forces.
Historical Patterns and What They Suggest
The Fear and Greed Index has no predictive nature, and history portrays that periods of Extreme Fear last months before they change into a neutral or greedy mood. As an example, in the 2021 2022 bear market, sentiment fell to fear deep for long periods before recovering with the revival of the price momentum in 2023.
Another paper by scholars that studies sentiment regimes in cryptocurrency markets points to the extreme sentiment, either fear or greed, as connected to increased volatility and a potential transition phase in the future when the selling pressure is drained, and the liquidity level stabilizes. Although this kind of research does not identify any specific date, it suggests that the results of such escalations to the extreme fear territory and then to the territory of greed indicate structural changes that go beyond the short-term price changes.
Further, other technical analysis frameworks indicate that deep sentiment lows along with oversold signs, like those of the Relative Strength Index (RSI) measurements, may represent a sustainable bottom period, out of which markets can develop an upward momentum. Such conditions have been observed in recent research and study reports where capitulation is seen to be almost complete before reversal sets in at the beginning of the year 2026.
However, when the sentiment is Greed, signified by an overall reading greater than 60 on the Fear & Greed Index, prolonged rallies in the price, participation of more participants (retail and institutional flows), and high levels of social involvement will be associated. All these are present, and sentiment is still in a very fearful land.
Macro Forces, Market Dynamics, and the Path to Greed
The interaction between the macroeconomic situation in the world and the crypto sentiment is one of the primary causes of the long-term fear situation in the crypto markets. In the late 2025 and early 2026, the digital assets have been burdened by the growing interest rate issues, regulatory uncertainty, and classic market volatility.
Although the price of crossovers indicated its strength in retaining its major support levels, the mood was still pessimistic due to the growing inclination of investors to consider cryptocurrencies as risky assets that are more susceptible to macroeconomic changes.
Nevertheless, investors following cycle bottoms and sentiment extremes now have possible indications of where the market is likely to go. The Matrixport sentiment index, which extends the Fear and Greed Index by capturing positioning and volatility, recorded readings of fear of below-zero, and this is a rarity, something the market has occasionally accompanied with a significant movement of the major trend. Such oversold sentiment is similar to past market bottoms before the trend switches.
Similar to this, long-term sentiment readings have recently reached their lowest level in four years, which implies that selling pressure amongst the large holders could be fading. Analysts at Matrixport view the change in their internal sentiment indicators as the selling pressure starting to ease, which is an indicator of the possible formation of a bottoming phase. This does not serve as a direct indicator of a Greed phase, but it does confirm the notion that market psychology might be at a point where it is no longer in a state of pure panic, but rather stabilization, which will be followed by a considerable amount of rebound.
The other significant possible trigger of sentiment improvement is renewed institutional adoption or optimistic regulatory changes. Earlier rallies, including 2020-2021 and 2023-2024, were boosted as institutional interest revived, coupled with better legal frameworks of crypto products such as Bitcoin ETFs. Should the same happen in 2026, they would offer the lever that is required to change the perception to optimism and ultimately greed.
When Might Greed Return?
Combining the existing sentiment data and historical cycles, technical indicators, and macro forces, most market analysts opine that short-term relief rallies can be experienced, but it will not likely be in an extended state of greed before more structural enhancements can be realized.
Technical analysts believe that in the short term (1-3 months), there is an indication of relief rallies whereby Bitcoin and major altcoins may experience moderately bouncing jumps.
This may elevate sentiment to a neutral level, although not to the extent of attracting a full Greed reading. Such rebounds can be driven by oversold situations and panic exhaustion as the traders make opportunistic positions.
Disclaimer
In line with the Trust Project guidelines, please note that the information provided on this page is not intended to be and should not be interpreted as legal, tax, investment, financial, or any other form of advice. It is important to only invest what you can afford to lose and to seek independent financial advice if you have any doubts. For further information, we suggest referring to the terms and conditions as well as the help and support pages provided by the issuer or advertiser. MetaversePost is committed to accurate, unbiased reporting, but market conditions are subject to change without notice.
About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
More articles
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
ChatGPT’s Popular Feature Now Available on Gemini: Use Your Camera to Talk with Gemini in Real TimeThe popular camera and screen sharing feature—previously known from ChatGPT—is now available on Gemini for both Android and iOS devices. At Google I/O 2025, the company announced that this feature is no longer exclusive to Pixel phones and is now being rolled out as a free update to all compatible devices.
Thanks to Gemini Live, you can now interact with the AI assistant by sharing your phone’s camera or screen. This allows for more natural and visual conversations. Instead of describing something verbally, you can simply show an object to the camera, enabling Gemini to analyze what it sees, such as identifying an animal species or recommending the right type of screw for a repair task.
✅ This feature is available now for Android and iOS users.
Deeper App Integration and Privacy Controls
Google also revealed that Gemini Live will soon be more deeply integrated with apps like Google Maps, Calendar, Tasks, and Keep. This will allow Gemini to offer more contextual and intelligent answers to your questions based on what it sees and what you’re working on.
When it comes to user privacy, Google has emphasized that users will have full control over which apps are integrated with Gemini. All permissions can be reviewed and changed at any time.
Originally launched only for Pixel devices last month, this powerful feature is now available to a much broader audience. You can start using it right away from your Android or iOS device.
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The new Gemini-based AI tool is now available, allowing users to edit their photos with simple voice or text commands. This advanced feature, which was first announced to celebrate the tenth anniversary of the Google Photos app, is set to revolutionize how users interact with their images.
The generative AI editing tool was initially introduced on the Pixel 10 series and is now being gradually made available to other Android phones. This wider rollout signals Google’s commitment to bringing powerful, easy-to-use AI technology to a broader audience.
How to Access the Generative AI Editing Tools
The feature is currently being offered to Android device users in the U.S. Before you can start using it, there are a few requirements: your Google account language must be set to English, the Face Groups feature needs to be turned on, and location estimates must be enabled. Once these steps are completed, you will be able to access the powerful new editing features.
This new tool suite is expected to change the way people edit their photos, making complex tasks simple and intuitive. Instead of manually adjusting colors or painstakingly removing objects, users can simply tell the AI what they want to do. For example, you can use a voice or text command to say, “make the sky brighter,” or “remove the person in the background,” and the AI will handle the rest. This shift toward a more conversational and command-based editing experience highlights the future of AI in consumer applications.
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YouTuber and engineer Luke Maximo Bell has developed a battery-free drone that runs entirely on solar power. The carbon fiber-bodied drone achieved a new first by taking off without energy storage.
As technology advances, we continue to see innovative ideas, especially in the field of aviation. Finally, YouTuber and engineer Luke Maximo Bell, who pushes the boundaries in drone technologies, has undertaken another unconventional project. Bell developed a drone that operates solely on solar energy without any battery, capacitor, or energy storage unit. The model can operate on energy received directly from the sun.
Takes Off Without Storing Energy
Bell’s project follows his recently developed Peregreen 3 drone, which reached a speed of 585 km/h. After the speed record attempt, the YouTuber has now created a productivity-focused design. As you might guess, designing a battery-less drone requires minimizing weight. Therefore, carbon fiber material was chosen for the body and propellers.
The power source is a long array of 27 small solar panels mounted directly on top of the drone. The panels are connected directly to the power system, transmitting energy instantly to the motors. It should be noted that the system struggled to stay airborne in initial tests, particularly due to its lightness. Changes in wind direction or the intensity of sunlight easily affect the drone’s balance. Despite this, Luke managed to fly the device successfully, albeit briefly, after a few adjustments. The drone was able to stay aloft using only sunlight, making the project technically “successful.”
Luke Maximo Bell states that the project is still in its initial stages. The new version will include more solar panels, a GPS module, and autonomous flight software. The goal this time is to break a Guinness World Record.
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AI agents are becoming a key enabler for businesses looking to streamline processes, automate repetitive tasks, and empower their employees to work more efficiently. In Microsoft 365 Copilot, we’ve already seen a lot of solutions that focus on improving productivity for individuals. Yet, the potential for AI-driven automation goes much further when you can connect intelligent , natural language, agents directly to your own business data and processes—enter Azure AI Agent Service in Azure AI Foundry.
In this post, you read about why AI Agents are valuable, and how Azure AI Agent Service makes it easy to build and customize these agents. I also did some testing and share those experiences, including the Code Interpreter feature for data analysis. Finally, in the end you can read through some quick tips on how you can get started.
What Are AI Agents and Why Should Businesses Care?Stories of Transforming Business ProcessesAI AgentsAzure AI Agent Service is now in Public PreviewMy Testing Experience with Code Interpreter and Knowledge SourcesCode InterpreterExternal Knowledge & RAG TestingAgent Configuration Made SimpleModel Tuning Options and Limitations Getting Started: The Quickstart PrerequisitesCreating and Testing Your AgentExpand with SDK or Additional ToolsConclusionRead more from these sources:About writing this article
At its simplest, an AI agent is a self-contained “microservice” powered by a large language model (LLM) or similar AI model. It’s designed to answer questions, perform actions, and ultimately automate or augment specific tasks. Let’s take a look at some examples first.
Stories of Transforming Business Processes
A Fictional Look at a Multi-Agent Sales EcosystemImagine a large electronics retailer that operates in dozens of countries. They have separate specialized AI agents for different aspects of the sales cycle. One AI agent handles lead qualification by scanning incoming inquiries and extracting key information about prospective clients. Simultaneously, another agent is responsible for product recommendations based on real-time pricing and inventory data. Once a lead is qualified, a scheduling agent sets up demos with sales reps and automatically books a meeting in Microsoft Teams, complete with relevant documents attached.
These agents can also collaborate, passing information to one another about lead status or the best product bundles for a particular region. Thanks to this multi-agent approach, a sales rep can jump in only when human interaction is truly needed, rather than juggling repetitive tasks like re-checking stock or manually coordinating meetings. The entire process is a well-orchestrated system that frees employees from repetitive admin and data entry. The result: more personalized interactions with customers, higher sales velocity, and a drastically reduced chance of human error.
Fujitsu: RAG and Sales Efficiency in the Real WorldWhile the above scenario is hypothetical, real-life businesses already leverage Azure AI Agent Service to revolutionize their sales processes. For example, Fujitsu leveraged Azure AI Agent Service and Semantic Kernel to build an AI-powered automation solution to streamline proposal creation, enabling sales teams to focus on high-value customer engagement. The AI agent dynamically retrieves and synthesizes data from dispersed sources, ensuring accuracy and relevance while integrating seamlessly into Fujitsu’s existing Microsoft ecosystem. “We are using Microsoft’s Semantic Kernel and Azure AI Agent Service to orchestrate multiple specialized AI agents and an orchestrator AI to coordinate them to answer questions as a team,”
Cineplex: Transforming Customer Service Through AutomationCineplex, a leading Canadian media and entertainment company, has transformed its customer service operations using AI-powered automation. One of its biggest challenges was handling refund requests, a time-consuming process that took 5–15 minutes per request. To solve this, Cineplex implemented an AI Copilot agent using Microsoft Power Platform and Azure AI. Now, guest service agents simply input a booking ID and date, and the AI handles the rest—retrieving data, validating the request, and completing the refund in about 30 seconds This highlights how AI agents can optimize routine tasks, boost efficiency, and enhance customer service—without replacing human interaction. For businesses looking to scale support operations, AI-powered automation can be a game-changer.
AI Agents
Unlike basic chatbots, AI agents can incorporate context from historical conversations and connect to external systems, allowing them to:
Search your company’s knowledge base or the web.
Process and interpret files or real-time data.
Make calculations, generate reports, even run code.
Perform complex tasks that save employees time and effort.
Integrate with other systems, internal and external
Engage other agents in the process: multi-agent systems
Cope a lot better with various situations better than traditional automation. This is due to LLM in their “core” giving understanding of the goal and what is needed. AI Agents are flexible and can adapt to situations – and also know when to ask help from an another agent or a real person.
In other words, AI agents can complement human workers by taking on repetitive or time-consuming jobs. That might mean a customer support agent that automatically retrieves answers from a knowledge base, an internal finance agent that crunches budget data from spreadsheets, or a sales agent that triggers email workflows.
From a business standpoint, AI agents have tangible benefits:
Accelerated decision-making: Dynamic, context-aware AI reduces manual research.
Scalability: Agents can work around the clock, handling tasks for multiple teams simultaneously.
Consistency: They apply knowledge and logic in a uniform way—fewer mistakes due to human error. Today is the time when we experiment with agents, and it needs to be realized agents can also make mistakes – sometimes even plenty.. The goal is in the consistency and coming up with new ideas where AI can transform the process, and these won’t be reached without experimenting, coming up with challenging use cases and courage to try out something new.
Azure AI Agent Service, now available as public preview in the Azure AI Foundry portal, provides a managed environment to build, debug, and deploy these AI agents. It’s designed so that developers and tech-savvy business users can quickly shape an agent’s capabilities without having to assemble all the underlying code or infrastructure themselves. This speeds up pro-code agent development and is yet an another example of fusion teams where business and developers work together.
Key capabilities include:
Ready-to-Go Tools & Integrations:
Code Interpreter: Allows agents to execute Python code within a secure sandbox—great for number-crunching, data analysis, or generating graphs.
Bing Search & Azure AI Search: Agents can pull in external knowledge from the web or your own data, adding relevant context to tasks.
Azure Functions Support (SDK-based): Developers can expose custom business logic or external APIs to the agent, letting it trigger real-world actions.
Conversational Memory:Agents can maintain a thread of conversation, remember details, and continue where you (or the agent itself) left off. This is handled securely on the server side.
Multiple Model Options:Although Microsoft’s GPT-4o is a popular choice, you can also deploy other partner models like Cohere or Mistral in the Azure AI Foundry. (Note: Mistral-large-2407 is becoming legacy and may not be available much longer.)
Basic vs. Standard Setup:
Basic Setup (supported in the Azure AI Foundry portal today): You rely on Microsoft-managed resources for storage and search. Quick to start, minimal overhead, but it offers less control.
Standard Setup (Bicep template–only): You bring your own resources (like Azure Storage and Azure AI Search) for complete visibility and cost management.
I’ve spent some time exploring the new Agents UI in Azure AI Foundry, putting these features to the test. Here’s what stood out for me:
Code Interpreter
A fun (though fictional) scenario was exploring the terminal velocity of a laptop falling from an airplane. With the agent’s Code Interpreter tool enabled, I could ask the agent to run physics-related calculations. It can generate quick math scripts in Python—and this is just a simple example about the Code Interpreter.
I uploaded an Excel file for the 2023 budget of the city of Vantaa (available as open data) to the Code Interpreter. The agent then read and interpreted the file, making it straightforward to analyze budget figures, gather insights, and visualize the data.
External Knowledge & RAG Testing
I also tested a scenario using basic RAG (retrieval augmented generation). By uploading some demo documents, the agent was able to pull targeted facts from my own content, weaving them into its answers. The RAG with AI isn’t anything new anymore, but the Assistants API working behind the hood isn’t an everyday tool yet. So it made sense to play around to see how it performs – and it was just like I expected.
Agent Configuration Made Simple
The visual flow in the Azure AI Foundry UI is deceptively simple: define your agent’s name, add Knowledge sources (files or indexes), and specify which Actions (tools) the agent may use.
Currently, the only action available from the UI is Code Interpreter. If you want to integrate your own, such as Azure Functions, you can do more via the SDK.
Model Tuning Options and Limitations
Basic tuning for Temperature and Top P is easily accessible in the UI, so you can adjust how creative or deterministic your agent’s answers should be.
In the UI, only Code Interpreter is displayed as an “action,” but the underlying Assistants API definition is flexible—new actions or custom tools can be added once they are enabled.
I experimented with GPT-4o, which worked seamlessly. The service also promises support for non-OpenAI models like Cohere and Mistral, though my free Azure subscription didn’t allow me to deploy them.
Overall, these tests highlight how quickly you can piece together a specialized AI agent that’s unique to your brand, team, or project. With a few lines of code or a few clicks in the UI, you can transform a simple chat model into a mini-assistant with real business value.
Want to try it yourself? Here’s a short guide based on the official quickstart.
Prerequisites
An Azure subscription (create a free trial if needed).
The Azure AI Developer role assigned. This gives you the right permissions to create and manage AI agents.
Basic Setup via the Azure AI Foundry Portal: Because the Foundry portal only supports the “basic setup,” you’ll be using Microsoft-managed storage and search behind the scenes. This gets you getting started fast.
Creating and Testing Your Agent
Navigate to Agents in the Azure AI Foundry portal and select “New agent.”
Provide a name and add instructions (e.g., “You are a business analyst specializing in forecasting.”).A tip: use Chat Playground’s Generate prompt feature to build instructions for the agent.
Under “Knowledge & Action,” add Code Interpreter if you want the agent to handle data analysis or code execution. You can also attach up to 20 files that your agent can read and use for generating outputs.
After configuring your agent, switch to the “Playground” to begin chatting.
You can revise instructions, tweak model parameters (Temperature, Top P), or add new knowledge files and tools.
Confirm that your agent is responding as expected and refine your instructions or data sources if needed.
To incorporate your own Azure Functions or external APIs, you’ll need to define them as tools via the Azure AI Foundry SDK or the Azure OpenAI SDK. This is particularly helpful for more complex automations where the agent might, for instance, update a CRM record or send an email on your behalf.
Azure AI Agent Service is a promising step forward in automating diverse business processes—from data analysis and RAG queries to more action-oriented tasks like connecting to external APIs. The combination of large language models, integrated tools, and simple setup in the Azure AI Foundry UI makes it a compelling choice for trying out a variety of automation scenarios. In the future (near, I hope) we can also add multi-agent systems to this.
For business decision makers, one key factor is how quickly and securely it is possible achieve operational benefits (and ROI). Whether you’re in finance, manufacturing, retail, or beyond, AI agents offer a new way to tap into supercharging business processes. Think scaling processes that traditionally depend on human intervention, to agent-driven that improve productivity, reduce manual errors, and freeing tedious work (and precious) time from humans. When I talk with customers about Microsoft 365 Copilot, it already helps many to complete more tasks faster than before. For many of them, that means less long days turning evenings – or that pile of to do tasks stays in control.
If you’re curious, I recommend checking the quickstart, spinning up a basic agent, and giving Azure AI Service UI and especially the Code Interpreter with Assistants API a try. From data crunching to helping your sales or support teams, you can see how fast you can build an pro-code agent core capable of meaningful work.
Read more from these sources:
Yes, I used again the Azure OpenAI Service reasoning model o1 to help me out with this. I provided the model a long prompt, that included my goal, insights, information of what I did and what I wanted to express in the post. Along with the background information from Microsoft Learn and articles. After that I used some prompts to refine the result and added example use cases. Finally I coped the text to the blog and went through this – applying changes, deleting parts and adding new insights, and of course pictures. This speeded up the actual blog writing process quite a lot, but it still took a few of hours in total.
Perhaps for one blog post I will create a Teams meeting, that I record and transcribe, when I testing out new feature. Using that could provide quite an unique base for the post draft, that I generate with the help of o1. That would not be so structured as writing my selected insights, but would definitely be a different way. Will it be faster? That I can find out by testing it out.
The next crypto bull run won’t just be about Bitcoin or Layer 1 giants, it’ll be driven by gaming blockchains with real players, real ecosystems, and real utility. From high-speed performance to massive developer networks, these five platforms. Sui, Ronin, Polygon, Immutable, and Beam aren’t just hyped, they’re already building the future of Web3 gaming.
Key Takeaways
Sui brings ultra-fast parallel processing and the Move language to supercharge interactive, object-based game design.
Ronin is a battle-hardened chain built by Axie Infinity’s creators, now onboarding legacy gaming IPs.
Polygon leverages its AggLayer to unify chains and power cross-chain gaming on Ethereum.
Immutable X dominates NFT gaming infrastructure with over 625 games and gas-free transactions.
Beam, backed by Merit Circle DAO, is evolving into a dedicated gaming Layer 1 with deep industry integration.
Sui Network: Web3’s High-Performance Gaming Engine
Sui isn’t just another smart contract platformit’s purpose-built for gaming. Developed by Mysten Labs and launched in 2023, it uses a unique parallel execution engine combined with the Sui Move language. That means faster performance, dynamic NFTs, and complex gameplay mechanics that mimic real-world asset- onership.
Its object-centric model lets in-game assets evolve, interact, and own other objects. Think RPG characters upgrading weapons that also have their own histories. It’s tailor-made for developers who want to go beyond basic NFTs and create truly immersive games.
Sui’s ecosystem is ramping up with over 150,000 active addresses and games launching weekly, including titles from Orange Comet, Aether Games, and Worlds Beyond. Mysten Labs has formed over a dozen studio partnerships. Tools like the Sui Devnet and game SDK are simplifying onboarding.
Catalysts for 2025 include the SuiPlay 0X1 handheld console, designed to run blockchain-native games on-chain, and the introduction of dynamic NFTs, which will reshape game asset utility. Massive institutional backing from Coinbase Ventures, a16z, and Binance Labs adds legitimacy.
With an all-time high of $5.36 and more room to grow as adoption spreads, SUI offers both cutting-edge tech and high-upside potential. It’s a first-mover in object-based smart contracts and could redefine how assets function in Web3 gaming.
Ronin: The Proven Gaming Chain That Prints Revenue
Ronin has already done what many chains are trying to do: support a game that brought in millions of users. Built by Sky Mavis for Axie Infinity, it sidestepped Ethereum’s congestion by creating its own lightweight chain focused entirely on gaming.
Ronin now powers over $4.3 billion in NFT volume and has seen more than 17 million wallet downloads. Its infrastructure, including Katana DEX and Mavis Market, makes it a full-service chain for both players and developers.
In 2025, Ronin is transitioning from a niche to a mainstream platform. Recent partnerships with Act Games bring household brands like Hello Kitty, Zoids, and Bubble Bobble into the fold. These IPs have multigenerational appeal, offering a direct line to millions of traditional gamers.
Upcoming catalysts include the launch of permissionless development, which opens the Ronin ecosystem to all builders. The network is also deploying a $13 million DeFi fund, with a focus on staking, farming, and liquidity pools to drive TVL.
The RON token supports governance, validation, and staking—with rewards structured to incentivize long-term holding. It uses a DPoS model that enhances decentralization while maintaining throughput.
If you’re looking for a proven chain that has weathered the worst and is now expanding rapidly, Ronin is it. With new IPs, more games, and improved accessibility, the 2025 bull run could push RON well beyond its previous high.
Polygon: The Cross-Chain Powerhouse for Web3 Gaming
Polygon has evolved far beyond its MATIC roots. As Ethereum’s most advanced scaling solution, it powers thousands of dApps—and its focus on gaming has made it the go-to platform for developers seeking speed, interoperability, and low fees.
Polygon’s AggLayer, launched in 2025, is its masterstroke. It unites fragmented Layer 2 ecosystems, enabling seamless liquidity sharing and cross-chain gaming experiences. This means players can interact across games and platforms with minimal friction.
Its POL token introduces hyperproductive staking, allowing holders to secure multiple Polygon-powered chains and earn rewards from each. This structure encourages long-term engagement and aligns incentives between users and infrastructure.
Gaming partnerships are robust. The collaboration with Immutable zkEVM has yielded a game-optimized environment ideal for high-throughput transactions and NFT interoperability. Polygon is also home to studios and projects exploring dynamic gameplay, high-frequency trading, and esports integration.
Catalysts in 2025 include the Gigagas upgrade, which aims to achieve over 5,000 TPS by year-end. Polygon is also driving adoption with enterprise partnerships, including Stripe, BlackRock, and several legacy payment processors.
With prices still well below ATHs, POL offers upside from both gaming and broader DeFi and enterprise integrations. Its infrastructure-first approach makes it one of the most reliable plays in the space.
Immutable X: The NFT Gaming Giant
Immutable has quietly built the largest dedicated NFT gaming network in Web3. With over 625 games already integrated, including hits like Gods Unchained, Illuvium, and Guild of Guardians, it’s clear the platform has strong product-market fit.
The magic lies in its tech stack: zk-rollups from StarkWare power gas-free NFT minting and trading, all while maintaining Ethereum-level security. This allows developers to offer seamless player experiences without worrying about costs or congestion.
IMX is at the center of this ecosystem. It pays protocol fees, fuels staking rewards, enables governance, and even serves as in-game currency for many titles. Over 14 million IMX tokens are currently staked, showing high conviction from the community.
The big move in 2025 is the merger of Immutable X and zkEVM into a single unified chain: Immutable Chain. This gives developers EVM compatibility while preserving Immutable’s performance advantages. It also unlocks third-party DeFi tools, ERC-1155 liquidity, and better asset portability.
Game developers using Immutable benefit from the Immutable Passport, a frictionless identity and wallet solution, and the Global Orderbook, which ensures all NFT listings are instantly visible across marketplaces.
With new airdrops like Treeverse’s $END token rewarding stakers and institutional partnerships ramping up, IMX is primed to be the premier chain for NFT gaming. Price forecasts show potential gains of 250% to 350% in the near term.
Beam: The DAO-Powered Gaming L1 With Built-In Funding
Beam is the underdog that’s coming in hot. Created by Merit Circle DAO, Beam is focused solely on gaming and is backed by a treasury exceeding $100 million. This isn’t theory—it’s fully funded innovation.
Originally launched as an Avalanche subnet, Beam is now preparing for its Horizon upgrade that will transform it into an independent Layer 1. This means more decentralization, validator rewards, and a governance model controlled by the gaming community itself.
The Beam ecosystem includes over 60 active games, including Age of Battles, Space Nation, Goon Wars, and Megaweapon. Developers can use the Beam SDK and BeamOS to build and distribute games easily. Its Sphere Marketplace is tailor-made for NFT assets, offering a player-centric approach to asset trading.
The BEAM token isn’t just a gas token. It’s used for payments, staking, and DAO voting. More than 38% of the original supply has already been burned, adding serious deflationary momentum.
Upcoming catalysts include the launch of validator nodes, full staking functionality, and a major expansion to Immutable zkEVM, which will open the Beam ecosystem to even more users. With Avalanche Foundation support and a growing developer base, Beam is positioning itself as a real contender.
Still trading under $0.05, BEAM is the kind of asymmetric bet that can surprise everyone in the next market cycle if you catch it early enough.
Where the Next Wave Is Coming From
The next bull market won’t be driven by speculation alone. Real adoption, real users, and real games will be the key to breakout performance.
These five blockchains are already showing what’s possible when you mix smart infrastructure with visionary development. Whether it’s Sui’s dynamic NFTs, Ronin’s massive player base, Polygon’s multi-chain dominance, Immutable’s NFT expertise, or Beam’s DAO-driven growth, each has a unique edge.
They’re not betting on gaming. They are gaming. And as the market heats up, these tokens won’t stay cheap for long.
Watch them. Accumulate them. Or be left behind.
Frequently Asked Questions
Here are some frequently asked questions about this topic:
What is the best blockchain for gaming in 2025?
While each offers unique strengths, Sui and Immutable stand out for performance and NFT integration, while Ronin leads in mainstream adoption.
Which gaming blockchain has the most active users?
Ronin currently holds the edge with millions of wallet downloads and a proven track record supporting Axie Infinity’s massive user base.
What makes Sui different from other gaming blockchains?
Sui uses parallel processing and an object-based programming model with the Sui Move language, enabling dynamic, interactive game assets.
Is BEAM a good investment for gaming-focused crypto exposure?
Beam offers high upside potential with DAO backing, aggressive token burns, and over 60 games onboarded—though it’s still an emerging player.
How does Polygon support cross-chain gaming?
Polygon’s AggLayer allows seamless cross-chain asset and user transfers, making it ideal for developers building scalable and interoperable games.
Published: June 24, 2025 at 6:00 am Updated: June 24, 2025 at 6:25 am
by Ana
Edited and fact-checked:
June 24, 2025 at 6:00 am
To improve your local-language experience, sometimes we employ an auto-translation plugin. Please note auto-translation may not be accurate, so read original article for precise information.
In Brief
NAVI Protocol, OKX, and the Sui Foundation have launched a two-month initiative to introduce incentivized xBTC lending and borrowing on the Sui network.
Decentralized finance (DeFi) platform NAVI Protocol, operating on the Sui network, has established a time-limited partnership with centralized exchange OKX and the Sui Foundation to introduce xBTC lending and borrowing over a two-month period. The initiative aims to broaden the practical applications of xBTC, contributing to the development of Bitcoin-focused DeFi services within the Sui ecosystem.
The partnership offers xBTC liquidity providers access to borrowing incentives in Sui and USDC, in addition to rewards for liquidity provision. These measures are intended to increase the functional integration of xBTC, enabling users to optimize their BTC-based assets through supported borrowing mechanisms. This approach is expected to expand xBTC activity on Sui, resulting in improved liquidity and more robust network participation.
As part of the program, OKX will distribute SUI token incentives via its OKX Earn platform, while NAVI Protocol will allocate $500,000 in NAVX rewards to support user engagement during the campaign.
OKX Launches $200K SUI Incentive Program To Boost xBTC Lending On NAVI Protocol With Phased Rollout Starting June 24
In addition, OKX will allocate $200,000 in SUI token incentives to users who provide xBTC through the OKX Earn platform and engage in borrowing activities on NAVI Protocol. The incentive structure is designed to encourage active participation and support the broader development of the integrated DeFi ecosystem.
The campaign will follow a phased rollout. Incentivized borrowing pools for xBTC will be activated on NAVI Protocol starting June 24th. On June 27th, borrowing incentives will become available for users contributing USDC liquidity. By July 7th, the program will extend to include incentives for SUI liquidity providers.
“By partnering with OKX, we’re bringing xBTC to Sui to enhance Bitcoin’s DeFi utility. Users can supply and borrow against BTC with incentives, advancing cross-chain access and pushing scalability for the #1 crypto asset in the industry. We’re committed to connecting deep liquidity with practical DeFi applications,” said Elliscope Fang, co-founder of NAVI Protocol, in a statement to Mpost. “Following this partnership with OKX, we are planning to link token locks to governance and rewards, empowering users to shape NAVI Protocol’s decentralized future on the Sui blockchain,” he added.
This collaboration highlights NAVI Protocol’s broader aim of expanding access to DeFi while reinforcing Sui’s role as a prominent network for Bitcoin-based financial applications. Participants engaging through NAVI’s interface or via OKX Earn gain access to substantial liquidity and time-limited incentives made available through the initiative.
Disclaimer
In line with the Trust Project guidelines, please note that the information provided on this page is not intended to be and should not be interpreted as legal, tax, investment, financial, or any other form of advice. It is important to only invest what you can afford to lose and to seek independent financial advice if you have any doubts. For further information, we suggest referring to the terms and conditions as well as the help and support pages provided by the issuer or advertiser. MetaversePost is committed to accurate, unbiased reporting, but market conditions are subject to change without notice.
About The Author
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
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Alisa Davidson
Alisa, a dedicated journalist at the MPost, specializes in cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
