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ACI quantitative robot-The power of reading the trends

Published

5 years ago

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In 1962, Everett-Rogers proposed the theory of innovative diffusion, designed to explain how, why, and how quickly new ideas and technologies were spread. The theory explains how a product or technology gains momentum and spreads across a specific population over time. The end result is that people apply a product, technology, or idea. One of the key implications is that the application of a new technology in the population does not occur simultaneously. Instead, certain people and groups are more likely to apply technology at different times, consistent with specific psychological and social characteristics. There are five established applicationcategories for new ideas or products. These categories are defined below.

A The Innovator. “Innovators are adventurous and willing to take the risks. They fundamentally wanted to be the first person to try something new. Their goal is to explore new technologies or innovation and to find opportunities to be drivers of change. 」

B Early App. “Once the benefits of a new innovation start to become obvious, early apps are eager to try. Early apps bought new technology to achieve revolutionary breakthroughs that gave them a huge competitive advantage in their industry. They like to gain more advantages than their peers, and they seem to have the time and money to invest. 」

C Early majority. “The early majority of the mainstream usually focused on innovation in solving specific problems. They look for complete products that are fully tested, adhere to industry standards, and are used by others they know in the industry. They are looking for gradual, proven ways to do what they are already doing. 」

D Later majority. “The late most are risk aversion, applying only new innovations to avoid the embarrassment of being left behind. 」

E The Times. “The outdated people stick to the end. They valued traditional methods of doing things and refused to apply new technologies until they were eliminated by previous systems and forced to do it. 」

Bitcoin has captured the human imagination. Bitcoin’s story is perhaps more tempting than any previous high-tech innovation. It brings the most cutting-edge innovation to one of the foundations of mankind: currency. Given the possibility of revolutionizing such a fundamental concept, Bitcoin underwent several speculative cycles in its brief history. However, it would be a serious mistake to use these cycles as grounds for denying Bitcoin. These cycles are a well-understood psychological phenomenon caused by man’s fascination with new things. Moreover, any excessive emphasis on foam is to see the trees without the forest. Because, in just 12 years, Bitcoin has grown to 135 million users worldwide, with a faster application rate than the Internet, mobile phone, or virtual banking tools, namely PayPal, in the comparable period. At the current application rate, Bitcoin will reach 1 billion users in four years. Bitcoin, like all previous innovative technologies, is following a predictable and transparent application curve, although accelerating.

Such an incremental user base, the dividend period retained to us ordinary people about how long still?

Which track should we choose during the dividend period, and what can we can and do on this track?

These will be left for everyone to sink down to think;

For me personally, why I choose quantitative trading this derivative as a long-term development track, why I choose ACI quantitative robot, below I explain this question from two aspects.

First, the above mentioned Bitcoin development rate and user growth base, then for this market must be more and more user growth base, because this is the market of mankind, is Bitcoin’s original design concept —— decentralization, in the future, more and more people will enter the huge market derived from the digital currency such as bitcoin, Ethereum; the longer time period, one year, two years or five years, this cycle youcan grasp the number of your wealth appreciation (the biggest wealth);

Second, the first thing new users enter the market must face the secondary market, retained in the secondary market will learn currency speculation and trading, so what is the biggest difference between quantitative and labor? To enter the secondary market to do trading, the first is to learn mathematics, physics and chemistry, the second is anti-humanity, to face and accept the market of every market fluctuations, the third is to establish a set of their own trading system and resolutely implement. These three points seem simple, but need the hard conditions: 1, talent; 2, systematic learning and combat; 3,5 or even over 10 years of full-time experience; otherwise why there has been a saying: one profit, two draws, two losses and seven losses. Ask, if every user can make money in the digital money market, where does the money come from? And quantitative trading it is more suitable for ordinary players, it also has a scientific name called algorithm trading, it will replace artificial strategy, with mathematical models and scientific strategy, to achieve a certain conditions, but its profit is a stable long-term absolute value, rather than the short term of wealth; because each of us enter the digital currency secondary market, the original intention is to improve life, achieve wealth growth, increase the happiness index;

Third, why do you choose the ACI quantitative robot as a tool to fry the currency?

1. Select any product to make a comparison, especially the financial industry; here put forward a core: withdrawal rate is linked to risk, and the secondary market price of digital currency fluctuates greatly, a careless will be a large withdrawal, so we choose the product is not its return rate, but two products, product recovery rate is 100%, and 50%, product 20 year rate is 70%, and the withdrawal rate is 10%, the choice is only product 2;

2. Fund utilization rate, not just play finance, as long as you do business you will understand that the nature of business is not related to fund utilization, the greater your capital utilization proves that the more you can do, the more pipeline to profit; (those who play Martin strategy)

3. The concept reflected by the ACI quantitative robot is also consistent with the personal development ideal, It is free and continuously updated and optimized for life, Of course there is no free lunch, After all, everything takes costs, It charges a small transaction fee, To mark 99.99% of the various products on the current market, All exceptions are the lowest 20% profit withdrawals, Take an example here, If 10,000 u profit 1,000 u, Excluding withdrawal servants and exchange fees, Only over 700 u, came up with While the same ACI quantized robot profits 1,000 u, with 10,000 u Remove fees, Final hand 935-940u;

4. API technology interface of trading platform, do quantitative is a core is security and stability, as the three head compliance trading platform —— currency network, I think I don’t need me to introduce, whether from the user base, trading depth or technical security, is the best choice, after all, security and stability is not what we want;

Simply summary, quantification is actually statistics

About Author

Alex Jacob

Alex Jacob is a literature author. He was born in Chicago. Alex passion is writing news articles. He writes number of articles and published it.

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Press Release

Giggso Introduces Raven, Andie, and AIRTaaS to Help Enterprises Bring Discipline, Reasoning, and Security to AI Adoption

Published

5 hours ago

on

May 26, 2026

By

TROY, Mich., May 26th, 2026, ZEX PR WIRE — Enterprises are moving faster with AI than ever before. But many are also quietly losing comprehension of the systems they are building.

Engineering teams now generate code, workflows, automations, and AI-driven decisions at unprecedented speed using tools like Claude, Codex, Cursor, and enterprise copilots. While productivity has increased, organizations are also experiencing a new operational challenge: more meetings, fragmented workflows, inconsistent outputs, security concerns, architecture drift, and growing difficulty understanding how systems actually work together.

Giggso calls this problem “comprehension debt” — the growing gap between AI-generated velocity and organizational understanding.

Today, Giggso announced Raven, Andie, and AIRTaaS, three offerings designed to help enterprises reduce comprehension debt and bring discipline, reasoning, and continuous security testing into AI adoption at scale.

Together, the offerings form the front door into GSD (Giggso Security Domain), Giggso’s broader architecture for governing, securing, and operationalizing enterprise AI systems.

“At a small scale, AI feels magical,” said Ravi Venugopal, Founder and CEO of Giggso. “At enterprise scale, it can quickly become operational chaos. Teams move faster, but understanding drops. Meetings increase. Ownership blurs. AI starts producing more than organizations can realistically comprehend or govern. That is the problem we are solving.”

At the center of the announcement is Raven, Giggso’s discipline layer for AI-assisted software development.

Raven is designed to help organizations enforce engineering discipline inside AI-driven development workflows before problems reach production. Rather than acting as a traditional code scanner after development is complete, Raven introduces governance, architecture awareness, policy enforcement, and review controls directly into AI-assisted coding environments.

The platform helps organizations identify risks such as:

  • architecture drift
  • unapproved libraries
  • exposed secrets
  • policy violations
  • insecure dependencies
  • undocumented AI-generated logic
  • uncontrolled AI usage patterns

The goal is not to slow development, but to preserve organizational understanding as teams move at AI speed.

“AI can now generate code faster than teams can comprehend it,” Ravi said. “Without discipline, enterprises accumulate technical debt, security exposure, and operational confusion at machine speed. Raven helps organizations preserve engineering quality and architectural understanding while still moving fast.”

Giggso also introduced Andie, a structured reasoning engine designed to help enterprises improve contextual thinking and operational decision-making across teams.

Unlike traditional chatbot-style AI interfaces that generate isolated answers, Andie is designed to help organizations reason through problems with context, constraints, and multiple perspectives in mind. The platform is intended to support operational workflows across delivery, strategy, planning, support, and execution environments.

Giggso believes one of the biggest failures in enterprise AI adoption is not a lack of intelligence, but a loss of shared understanding.

“Most organizations do not need another chatbot,” Ravi said. “They need systems that help teams think more clearly together. AI should reduce confusion, not multiply it. Andie is designed to strengthen organizational reasoning, preserve context, and reduce the fragmentation that happens when every team operates with disconnected AI outputs.”

To address the growing security risks around enterprise AI adoption, Giggso is also expanding AIRTaaS, its AI Red Teaming as a Service platform.

As enterprises deploy AI agents, copilots, retrieval systems, and autonomous workflows into production, traditional security testing approaches are increasingly insufficient. AI systems can fail through prompt injection, hallucinations, role-boundary violations, tool misuse, unsafe autonomy, data leakage, and adversarial manipulation.

AIRTaaS continuously stress-tests AI systems against these real-world failure scenarios before they become operational incidents.

The platform combines:

  • AI red teaming
  • observability
  • governance workflows
  • incident tracking
  • remediation guidance
  • human-led adversarial testing

To strengthen its execution capabilities, Giggso has partnered with Seiance India, a woman-owned AI security startup based in Chennai, India, whose product, Trinity, is an AI security and observability platform.

“AIRTaaS turns AI security into an operational discipline instead of a compliance checkbox,” said Abhinaya, CEO of Seiance India P Ltd.
“Enterprises need continuous stress testing because AI systems are constantly evolving. Our focus is helping organizations identify weaknesses early, validate resilience continuously, and improve trust in production AI systems.”

Giggso also announced that portions of AIRTaaS and related tooling will be free for Individual Developers, while core Enterprise developer-focused red teaming capabilities will be low-cost and easy to certify for teams.

The company said the decision reflects a growing concern about “AI washing” — where organizations overstate AI capabilities without sufficient operational rigor — and the rise of “AI slop,” low-quality AI-generated outputs that appear acceptable on the surface but fail under real operational conditions.

“We believe AI adoption needs more honesty, more discipline, and far more operational accountability,” Ravi said. “The future belongs to organizations that can scale AI without losing security, comprehension, governance, and trust in the process.”

Raven, Andie, and AIRTaaS are part of GSD (Giggso Security Domain), Giggso’s enterprise architecture for governing AI systems, coding workflows, observability, orchestration, reasoning, and AI operational security across the enterprise.

More information is available at Giggso

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Cloud PR Wire

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Press Release

Caladan Launches API Liquidity: Institutional Access to Aggregated Digital Asset Liquidity Across 100+ Tokens

Published

8 hours ago

on

May 26, 2026

By

Singapore, May 26th, 2026, ZEX PR WIRE — Institutional counterparties can now access executable streaming prices and RFQ liquidity for spot and perpetuals on 100+ digital assets through the Caladan API, launched today by Caladan, the largest Asia-headquartered market maker for digital assets.

Built on nearly a decade of active trading, Caladan continuously aggregates pricing and depth from 20+ on-chain protocols, 47+ centralised exchange integrations, and bilateral relationships. The result is a single pricing feed that delivers tighter spreads, higher fill rates, and full depth on long-tail tokens.

“Fragmentation is the defining liquidity challenge in digital assets today. A single exchange, a single counterparty, or a single OTC desk will always have an incomplete view of price and depth. We have spent nine years building the infrastructure to see the whole market simultaneously, and API Liquidity makes that infrastructure available to institutional participants through a single API connection.” – John Gu, CEO, Caladan

Why aggregation produces better pricing

Digital asset liquidity is highly fragmented across centralised exchanges, decentralised protocols, regional venues, bilateral broker-dealers, and OTC desks. Caladan’s sourcing model is the commercial differentiator. The firm facilitates over $170 billion in annual trading volume across more than 100 assets, which means its pricing engine is continuously calibrated against a wider range of market signals. The more heterogeneous the sourcing — on-chain, off-chain, bilateral, and platform-routed simultaneously — the tighter the spread and the deeper the available size at any given price point.

The broadest token coverage of any market maker

API Liquidity provides access to the top 100 tokens — the widest token coverage available from any market maker globally. Coverage spans spot and perpetuals.

For institutional participants managing diversified digital asset portfolios or building crypto-embedded products, this breadth eliminates the need to maintain multiple liquidity provider relationships to cover the full token universe.

Flexible connectivity and settlement

API Liquidity is designed for immediate integration with minimal development overhead. Counterparties can connect through the channel that fits their existing workflow:

  • Direct API: Native FIX connectivity (4.2, 4.4, 5.0) for firms that prefer a direct bilateral connection

  • Platform partners: Desks already connected to Talos, Finery Markets, or CrossX can access Caladan liquidity with no additional integration work

Settlement is handled through institutional partners, with options for fiat and stablecoins:

  • Hidden Road and BitGo Go Network for custodial settlement

  • Customers Bank CUBIX for fiat settlement in USD

  • USDT and USDC settlement available directly

Competitive credit and margin terms are available for qualifying counterparties. Fiat currency pairs including EUR and JPY are in development, with additional currencies in the pipeline.

About Caladan

Caladan is Asia’s largest digital asset market maker, headquartered in Singapore with teams across seven global offices. Since 2017, Caladan has facilitated over $170 billion in annual trading volume, operating across 65+ exchanges worldwide. The firm provides market-making, OTC trading, DeFi expertise, and investments to institutional participants globally.

About Author

Cloud PR Wire

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Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

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Press Release

Caladan Launches API Liquidity: Institutional Access to Aggregated Digital Asset Liquidity Across 100+ Tokens

Published

8 hours ago

on

May 26, 2026

By

Singapore, May 26th, 2026, ZEX PR WIRE — Institutional counterparties can now access executable streaming prices and RFQ liquidity for spot and perpetuals on 100+ digital assets through the Caladan API, launched today by Caladan, the largest Asia-headquartered market maker for digital assets.

Built on nearly a decade of active trading, Caladan continuously aggregates pricing and depth from 20+ on-chain protocols, 47+ centralised exchange integrations, and bilateral relationships. The result is a single pricing feed that delivers tighter spreads, higher fill rates, and full depth on long-tail tokens.

“Fragmentation is the defining liquidity challenge in digital assets today. A single exchange, a single counterparty, or a single OTC desk will always have an incomplete view of price and depth. We have spent nine years building the infrastructure to see the whole market simultaneously, and API Liquidity makes that infrastructure available to institutional participants through a single API connection.” – John Gu, CEO, Caladan

Why aggregation produces better pricing

Digital asset liquidity is highly fragmented across centralised exchanges, decentralised protocols, regional venues, bilateral broker-dealers, and OTC desks. Caladan’s sourcing model is the commercial differentiator. The firm facilitates over $170 billion in annual trading volume across more than 100 assets, which means its pricing engine is continuously calibrated against a wider range of market signals. The more heterogeneous the sourcing — on-chain, off-chain, bilateral, and platform-routed simultaneously — the tighter the spread and the deeper the available size at any given price point.

The broadest token coverage of any market maker

API Liquidity provides access to the top 100 tokens — the widest token coverage available from any market maker globally. Coverage spans spot and perpetuals.

For institutional participants managing diversified digital asset portfolios or building crypto-embedded products, this breadth eliminates the need to maintain multiple liquidity provider relationships to cover the full token universe.

Flexible connectivity and settlement

API Liquidity is designed for immediate integration with minimal development overhead. Counterparties can connect through the channel that fits their existing workflow:

  • Direct API: Native FIX connectivity (4.2, 4.4, 5.0) for firms that prefer a direct bilateral connection

  • Platform partners: Desks already connected to Talos, Finery Markets, or CrossX can access Caladan liquidity with no additional integration work

Settlement is handled through institutional partners, with options for fiat and stablecoins:

  • Hidden Road and BitGo Go Network for custodial settlement

  • Customers Bank CUBIX for fiat settlement in USD

  • USDT and USDC settlement available directly

Competitive credit and margin terms are available for qualifying counterparties. Fiat currency pairs including EUR and JPY are in development, with additional currencies in the pipeline.

About Caladan

Caladan is Asia’s largest digital asset market maker, headquartered in Singapore with teams across seven global offices. Since 2017, Caladan has facilitated over $170 billion in annual trading volume, operating across 65+ exchanges worldwide. The firm provides market-making, OTC trading, DeFi expertise, and investments to institutional participants globally.

About Author

Cloud PR Wire

See author's posts

Disclaimer: The views, suggestions, and opinions expressed here are the sole responsibility of the experts. No Digi Observer journalist was involved in the writing and production of this article.

Continue Reading

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