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Samsung Collaborates with Israel’s Credorax On Automated Blockchain Platform For Merchants

Samsung SDS, a division of the South Korean tech giant that provides IT solutions, has partnered with Israel-based fintech and payment service provider Credorax, to tap the European payments market. The two firms will work together to build a blockchain-based settlement solution, which helps automate account reconciliation for European merchants and banks.

Inside Samsung’s Quest to Transform Payment Sector

The decentralized solution will use Samsung SDS’s Nexledger Universal blockchain platform to allow clients to automatically reconcile remittances, invoices, and payments with their bank records. The solution aims to develop efficiencies by automatically logging payment data on bank records and ledgers.

This solution will integrate into a payment platform, built using Samsung SDS’s Al-based technology, known as Brity Works, to automate various work processes. Based on this partnership, Samsung SDS is looking forward to entering the lucrative payments markets across Europe.

Hong Won-Pyo, Samsung SDS CEO and president, stated that the collaboration with Credorax, which already has offered solutions to firms across the wider European region, will enable the Korean tech giant to gain a foothold in the region’s payments sector. Hong Won-Pyo said, “Working in collaboration with Credorax, which specializes in providing payment solutions, will enable Samsung SDS to attempt to broaden its business in the European sectors that are in need to achieve digital transformation.”

Credorax works with e-commerce retailers and various merchants across the European Union and the European Economic Area.

A strategic plan to move into a lucrative business

On Feb. 18 2020, Samsung SDS changed its article of association to include e-finance as one of its key business areas. The firm clarified that the change was initiated to help new platform-based financial businesses that use big data and to enhance collaboration with other companies in the industry.

However, Samsung is also progressively making its move to enter into the blockchain arena. Its smartphones already support decentralized apps, developing a mobile-based blockchain ecosystem. The firm also has stakes in various blockchain startups, including blockchain startup Blocko hardware wallet maker Ledger, etc.

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Global Blockchain IoT Market Expected to Generate Returns Worth $5.8 Billion by 2026

The global blockchain IoT market is expected to offer a revenue of $5.802 billion by 2026, a study from Research Dive says.

With the internet of things (IoT) being increasingly implemented by many end-use industries across the globe, this is expected to be among the key drivers of growth in this sector. The finding shows a compound annual growth rate (CAGR) of 91.5% during the forecast period.

Furthermore, governmental initiatives on smart contracts and automation are anticipated to facilitate the development of the blockchain IoT market.

Per the report:

“The hardware sub-segment is expected to grow exponentially with a CAGR of 93.6% during the forecast period. Tenacious tasks incorporated by the hardware in IoT systems are expected to accelerate the growth of the blockchain market sub-segment during the forecast period.”

Ample opportunities are expected to create by the continuous technological advancements in the blockchain ecosystem. For instance, smart cities are forecasted to have a CAGR of 39.9% because blockchain triggers convenient data tracking, seamless transactions and minimizes security breaches.

Moreover, asset tracking and management are crucial in machinery supervision on the manufacturing floor. As a result, this factor is predicted to drive further growth in this sector.

Some of the key players in the blockchain IoT market include IBM Corporation, Amazon.com, the Ethereum Foundation, Intel Corporation, the Linux Foundation, Cisco Systems, and Microsoft Corporation.

In 2019, IBM revealed its intention to offer a blockchain and IoT solution to curb drone theft. This idea was coined because drones might steal packages instead of delivering them.

Therefore, IBM saw it fit to incorporate an IoT altimeter, which could be triggered if a liftoff happened. Furthermore, the altimeter could track the package’s information like attitude and store it on a blockchain platform.

Bybit Rolls Out Grid Bot for Automated, Seamless Futures Trading

Crypto exchange Bybit has launched a new trading bot for seamless and automated trading to tame price volatility and risk associated with futures trading.

The Bybit Futures Grid Bot seeks to democratize financial services by giving crypto users the chance to maximize their investments and time while trading. Per the announcement:

“Bots automates buy and sell orders when the price reaches preset prices. Bybit Futures Grid Bot sells futures contracts when the price is above entry and buys when below.”

The report added:

“By automatically buying low and selling higher, users profit from price volatility without the need to actively manage their positions. AI also allows preset parameters based on short/long/neutral positions.”

Bybit sees automation and artificial intelligence as stepping stones toward easy and affordable access to sophisticated trading environments.

Therefore, the Bybit Futures Grid Bot is the latest automated resource by the crypto exchange aimed at reducing downside risk in the futures market. Furthermore, it utilizes liquidity depth intended to minimize slippage.

Bill Xing, Bybit’s head of financial products, pointed out:

“Our Futures Grid Bot is part of our continuous efforts to simplify trading for our customers and accelerate the use of automation and AI.”

He added:

“Futures Grid Bot is a core element of our ongoing mission to level the playing field and democratize financial services, and is a perfect example of our trademark philosophy – innovation through iteration.”

The futures market has been experiencing various innovations. For instance, crypto exchange MEXC recently introduced the second-level K-line function to enhance real-time futures trading, Blockchain.News reported.

The second-level K-line function was to incorporate the one-second time period, given that the K-line chart usually accounts for minutes, hours, days, weeks, and months as time frames.

Scenarios for the Transition to Artificial General Intelligence (AGI)

The transition to Artificial General Intelligence (AGI) has been a topic of great interest and speculation in recent years. Many researchers and industry leaders believe that AGI, which refers to AI systems that can perform all tasks at human levels, may soon become a reality. In a working paper titled “Scenarios for the Transition to AGI,” economists Anton Korinek and Donghyun Suh delve into the economic implications of AGI development.

The paper starts by examining the relationship between technological progress, output, and wages. The authors propose a framework that decomposes human work into atomistic tasks with varying levels of complexity. They argue that advances in technology enable the automation of increasingly complex tasks, potentially leading to the automation of all tasks with the advent of AGI.

One crucial aspect analyzed in the paper is the race between automation and capital accumulation. If automation progresses slowly enough, there will always be enough work for humans, and wages may continue to rise. However, if the complexity of tasks that humans can perform is bounded and full automation is achieved, wages may collapse. The authors also consider the possibility of declines in wages before full automation occurs if large-scale automation outpaces capital accumulation, leading to an oversupply of labor.

The research suggests that the automation of productivity growth can result in broad-based gains in the returns to all factors of production. On the other hand, bottlenecks to growth caused by scarce, irreproducible factors may exacerbate the decline in wages. The authors emphasize the importance of understanding the distribution of tasks in complexity space and its impact on economic outcomes.

While the paper provides valuable insights into the potential consequences of AGI development, it also acknowledges the uncertainties surrounding the transition. The authors highlight that the distribution of tasks in complexity space plays a crucial role in determining the economic outcomes. They consider both unbounded and bounded distributions, with the latter reflecting the finite computational capabilities of the human brain.

Overall, the research by Korinek and Suh contributes to the ongoing discussion about the future of work in the age of AI and automation. By analyzing different scenarios for the transition to AGI, the paper sheds light on the possible effects on output, wages, and human welfare. It serves as a valuable resource for policymakers, researchers, and industry leaders seeking to understand the economic implications of AGI development.