iAgent protocol introduced an innovative AI-agent as digital asset class at Malaysia Blockchain Week in Kuala Lumpur and Asia Blockchain Summit in Taiwan this month, allowing gamers around the world to create, train, trade, and monetize personalized game AI-agents that take the NPCs of the past to a whole new level. iAgent protocol has developed the world’s first AI-agent trained from pro-players’ gameplay footage in Counter-Strike. This new AI asset class has the potential to spur a renaissance of innovation and growth within the gaming industry.

At both MBW and ABS, attendees received a first look at the revolutionary new class of digital gaming assets. iAgent Protocol presented new technology on August 1st and 6th, which uses AI Modules to train gaming characters based on gameplay footage. Their presentation featured an iAgent trained from the video footage of Flaxciz, a professional CS player from Team Secret.

iAgents are here to not only rehaul the outdated NPCs of the gaming world, but also to empower all gamers within the ecosystem. Any user can train an AI-agent with the gameplay footage and then trade, rent, and monetize their personal game agents. Whether it’s a casual gamer playing with friends, or an entire studio wanting to add world-class human-trained AI characters to their game, iAgent offers new solutions and possibilities.

In collaboration with Alliance, a global esports powerhouse competing at the forefront of the world’s most popular games, and Team Secret, a professional esports organization, iAgent was able to train a character based on the gameplay footage of Flaxciz.

Jamie Batzorig, CEO of iAgent and keynote speaker, unveiled the human-trained iAgent for the first time. The development team worked with AethirCloud, the project building scalable decentralized cloud infrastructure for Gaming and AI. Powered by DePIN, iAgent protocol leverages underutilized GPU resources from around the world and transforms them into a distributed GPU network dedicated to training AI-agents.

iAgent is supported by GEDA, a web3 esports ecosystem that is onboarding esports enthusiasts, and Emerge group, gaming marketing agency who have worked with well-known names like Valorant, Mobile Legends, and Riot Games.

The team at iAgent aims to democratize gaming by creating AI-agents as digital assets and providing all gamers with the tools and infrastructure to train their own Agents. These human trained AI-Agents represent players’ gaming strategies, styles, and creativity turning them into a digital representation of their gaming persona.

By creating the world’s first AI-agent trained on a pro esports player footage, iAgent is aiming to alter the landscape and future of gaming. The tools used to create this groundbreaking digital asset and gaming character will soon be available to everyone in the gaming ecosystem. A player only needs gameplay footage to develop their own AI-agent. With the first-of-its-kind AI_NFT standard (OFT), the creators will have full ownership over their AI-agents running on multiple chains using innovative technology developed by LayerZero Labs.

Liu Yi is among China’s 7 million ride-hailing drivers. A 36-year-old Wuhan resident, he started driving part-time this year when construction work slowed in the face of a nationwide glut of unsold apartments.

Now he predicts another crisis as he stands next to his car watching neighbours order driverless taxis.

“Everyone will go hungry,” he said of Wuhan drivers competing against robotaxis from Apollo Go, a subsidiary of technology giant Baidu (9888.HK)

China’s Ministry of Industry and Information Technology declined comment.

Ride-hailing and taxi drivers are among the first workers globally to face the threat of job loss from artificial intelligence as thousands of robotaxis hit Chinese streets, economists and industry experts said.

Self-driving technology remains experimental but China has moved aggressively to green-light trials compared with the U.S which is quick to launch investigations and suspend approvals after accidents.

At least 19 Chinese cities are running robotaxi and robobus tests, disclosures showed. Seven have approved tests without human-driver monitors by at least five industry leaders: Apollo Go, Pony.ai, WeRide, AutoX and SAIC Motor (600104.SS)

Apollo Go said in May it planned to deploy 1,000 robotaxis in Wuhan by year-end. In 2022, it had forecast it would be operating in 100 cities by 2030.

In a statement issued on Aug. 12, Apollo Go said it expected the transition to autonomous transport in China to be “gradual and well-regulated.”

“Our robotaxi fleet currently complements, rather than replaces, existing transport options,” the company said.
It added that the rollout of autonomous taxis would also create jobs at Apollo Go in monitoring and testing and in analysing the data gleaned from the ongoing trials.
Pony.ai, backed by Japan’s Toyota Motor (7203.T) operates 300 robotaxis and plans 1,000 more by 2026. Its vice president has said robotaxis could take five years to become sustainably profitable, at which point they will expand “exponentially”.

WeRide is known for autonomous taxis, vans, buses and street sweepers. AutoX, backed by e-commerce leader Alibaba Group (9988.HK) operates in cities including Beijing and Shanghai. SAIC has been operating robotaxis since the end of 2021.

“We’ve seen an acceleration in China. There’s certainly now a rapid pace of permits being issued,” said Boston Consulting Group managing director Augustin Wegscheider. “The U.S. has been a lot more gradual.”

Waymo is the only U.S. firm operating uncrewed robotaxis that collect fares. The company has a total of about 700 cars operating in San Francisco, Los Angeles, Phoenix and Austin, Texas, but not all of them are in service at all times, a company spokesperson said.

Reuters News

The African Development Bank (www.AfDB.org) and technology giant Intel have formalized their cooperation to transform the African digital ecosystem. The partnership aims to equip 3 million Africans and 30,000 government officials with AI skills.

Sealed at the recent African Development Bank’s Annual Meetings in Nairobi, Kenya, the deal will help create a critical mass of Africans proficient in Fourth Industrial Revolution (4IR) skills to accelerate growth and productivity and position Africans as contributors, not just consumers of 4IR. The training will address socio-economic challenges and boost productivity in key growth sectors such as agriculture, health, and education, thereby disrupting traditional growth cycles.

Bienvenu Agbokponto Soglo, Director of Government Affairs Africa and IGA CTO Liaison at Intel stated, “Intel looks forward to furthering its collaboration with African governments to make advanced technologies such as AI accessible to all, breaking down barriers related to geography, gender, and ethnicity, and enabling widespread participation in the digital economy.”

The partnership will also support African countries, regional economic communities, and continental organizations in developing harmonized policy and regulatory frameworks in AI, 5G, Wi-Fi 6E, data and cloud.

Ousmane Fall, African Development Bank’s Acting Director of Industrial and Trade Development, underscored the importance of digital skills for Africa’s youth. “With advancements in digital technology, our world is rapidly evolving, and so is our youthful population, projected to reach 830 million by 2050. To develop skills on a large scale and at the necessary speed, we need everyone’s cooperation,” he said. “The Bank is thrilled to collaborate with Intel to work towards this shared commitment. Together, we are shaping the digital future of Africa and empowering our youth.”

GITEX NIGERIA to debut in September 2025 connecting start-up innovators, AI experts, and young talents in Africa’s largest emerging digital economy; Introducing AI Everything Nigeria, North Star Nigeria, GITEX HealthTech 5.0 and GITEX Future Finance 5.0.

Following the two record-breaking and most verified editions of GITEX AFRICA Morocco, the continent’s largest tech and start-up show will expand to forge new opportunities specifically for the Nigerian ecosystem. The showcase and conference powerhouse is the most awaited event launch fueled by the mission to accelerate Nigeria’s national tech and start-up landscape in the most populous nation in Africa.

GITEX NIGERIA was announced today (30 May), during GITEX AFRICA Morocco the continent’s largest tech and start-up show, at a signing ceremony between KAOUN International, the overseas affiliated company of the Dubai World Trade Centre and organiser of GITEX, the world largest tech event brand, and the National Information Technology Development Agency (NITDA), the technology arm of the Ministry of Communications, Innovation, and Digital Economy of Nigeria.

The MoU was signed by Mr. Kashifu Inuwa Abdullahi, Director General of the National Information Technology Development Agency (NITDA) of Nigeria and Ms. Trixie LohMirmand, CEO of KAOUN International, organiser of GITEX globally, in the presence of Dr. Tunji Alausa, Hon. Minister of State for Health & Social Reform, Nigeria.

GITEX NIGERIA shall be the largest in-market access event of the decade to discover Nigeria’s vast tech ecosystem. It ushers the global tech community to fully explore the biggest and most valuable opportunities in this most populous African country, with the world’s most talented generation of tech and digital youths. Taking place in September 2025 in both Lagos and Abuja, the most strategic and business influential cities in Nigeria.

Addressing the media during the official announcement, the Director-General and CEO of NITDA, Kashifu Inuwa Abdullahi, said: “You can’t trade in isolation therefore we need to create a platform to accelerate trade in Nigeria. Presidential priorities include the acceleration of diversification through digitisation, industrialisation, manufacturing and innovation; to reform the economy to deliver sustained economic growth. The present mandate of our Ministry to accelerate the economy diversification by enhancing productivity in critical sectors, such as healthcare, education, and agriculture through technology and innovation. Bringing GITEX to Nigeria gives us the opportunity to export Nigerian technology to the world.”

CEO of KAOUN International, Trixie LohMirmand, organiser of GITEX NIGERIA, said: “The format of GITEX NIGERIA will be unique. It will enable the exploration of vast potential during a time when Nigeria is experiencing exponential growth impact in sectors such as AI, Health, Finance and Startups. We hope to co-create and multiply global partnerships to forge new opportunities for Nigeria across industries with the biggest societal betterment potential”.

GITEX in Nigeria shall spotlight the country’s exponential growth sectors in AI, Future Finance, Digital Health, Start-ups and Scale-ups. It will integrate the Nigerian tech ecosystem firmly into GITEX AFRICA Morocco and extend its reach into GITEX GLOBAL in Dubai and GITEX EUROPE in Berlin.

Reflecting core critical sectors aligned to the national digital strategy, GITEX’s most popular co-located shows will be introduced with the inaugural edition, including AI Everything Nigeria, North Star Nigeria for Startups, and the GITEX Health Tech 5.0 and GITEX Future Finance 5.0. The eagerly expected tech event will amplify in-market potential in the region’s fastest emerging country, with economic performance to grow 11.2% in 2024 according to the African Development Bank. 

Newsfile Corp., a leading newswire and regulatory filing service provider, is proud to announce the launch of LAUREL, a press release generation tool powered by Artificial Intelligence (AI). The tool is designed to assist content creators create concise well-crafted documents. LAUREL is now available to private companies via Newsfile’s Client Portal.

LAUREL provides a new level of convenience and efficiency for those who need to create press releases on a regular basis. With its user-friendly interface and advanced features, LAUREL is sure to become a must-have tool for content creators worldwide.

LAUREL uses a proprietary LLM, Large Language Model, that has been fine-tuned to ensure highly tailored results. Unlike other solutions on the market, LAUREL is internally hosted by Newsfile, which guarantees that any information uploaded remains secure and not shared to libraries on the Internet. The tool will be enhanced to include templates, suggestions, and more advanced features in the future. We invite feedback from our clients.

“We’re excited to launch LAUREL and offer our clients a powerful new tool to help them author their messages effectively. LAUREL facilitates the creation of press releases quickly and easily, without compromising security or confidentiality,” said Bill Batiuk, President of Newsfile. “LAUREL has been under development for more than a year and ensures that no information leaves our servers until dissemination. I would caution anyone using other AI tools that create press releases to question where their information is being sent during the creation process.”

–DISCO (NYSE: LAW), a leader in AI-enabled legal technology, announced today the launch of Cecilia doc summaries, a Cecilia AI feature that is now available for free to all current DISCO Ediscovery users. Cecilia doc summaries is a generative AI tool that provides detailed and high-level takeaways of individual documents at a user’s request, and lets legal teams sift through hundreds of pages of documents to find the information and facts that are most relevant to the case.

The nature of everyday legal work is evolving fast, as technology-enabled change continues to have a transformative impact on the industry. One challenge attorneys still face is having to parse through long documents and foreign language text, which can slow down review and lead to key pieces of information being missed. Cecilia doc summaries is a tool that lets teams expedite lengthy and tedious review processes, especially those with longer, more technical, or even foreign language documents, so they can more quickly orient themselves on the more important overarching themes within a specific legal document set. Users can easily, for example, distill the key points from a long report or contract; receive a comprehensive breakdown of a foreign language document in plain English; or obtain a summary of a new hot document found by Cecilia Q&A before sharing it with the case team — all with one click of a button.

“Over a short period of time, DISCO has made tremendous strides in delivering market-ready generative AI solutions, and we continue to be laser-focused on building products that provide tangible value to our customers,” said Kevin Smith, DISCO’s Chief Product Officer. “This is another example of how we are driving meaningful AI innovation in the space, and creating products that drive better outcomes for lawyers so they can shift their resources to focus on higher-value work.”

DISCO’s Cecilia AI platform includes generative AI offerings like Cecilia Q&A, a tool that allows users to ask natural language questions about the documents in their databases and receive detailed narrative responses along with specific source citations. Cecilia doc summaries is a feature within DISCO Ediscovery, a product that includes industry-leading AI tools for speeding up time to evidence. To learn more visit csdisco.com/offerings/ediscovery.

Forward-Looking Statement

This press release contains forward-looking statements regarding Cecilia doc summaries, including, among other things, the potential benefits derived from the use of Cecilia doc summaries, the impact of technology-enabled change on the legal industry, and DISCO’s ability to create products that drive better outcomes for lawyers. Words such as “may,” “should,” “will,” “believe,” “expect,” “anticipate,” “target,” “project,” and similar phrases that denote future expectation or intent regarding DISCO’s financial results, operations, and other matters are intended to identify forward-looking statements. You should not rely upon forward-looking statements as predictions of future events.

The forward-looking statements contained in this press release are subject to a variety of risks, uncertainties, and factors, including those more fully described in our filings with the Securities and Exchange Commission (“SEC”), including our Annual Report on Form 10-K for the year ended December 31, 2023, filed with the SEC on February 22, 2024. Further information on potential risks that could affect actual results will be included in the subsequent periodic and current reports and other filings that we make with the SEC from time to time, including our Quarterly Report on Form 10-Q for the quarter ended March 31, 2024. Forward-looking statements represent DISCO’s management’s beliefs and assumptions only as of the date such statements are made. We undertake no obligation to update any forward-looking statements made in this press release to reflect events or circumstances after the date of this press release or to reflect new information or the occurrence of unanticipated events, except as required by law.

The economic value of generative artificial intelligence (AI) to the world is immense. Research from McKinsey estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually.¹

But the energy cost of AI and its environmental impact can also be extensive unless our technology approach evolves to effectively tackle these challenges.

Current projections vary, but there are startling analyses of generative AI’s energy use and its impact on the environment. A peer-reviewed report in Joule projects AI energy use growing to over 85 terawatt-hours annually, more than the usage of many small countries (Ireland is the example given).² Popular studies, like those from Gartner, paint dire pictures of the environmental impact and the expense of adapting our computing infrastructure to generative AI. Gartner’s report predicts that by 2030, AI could consume up to 3.5% of the world’s electricity.³

Additionally, data center processing requires cooling, and cooling consumes water. In its latest environmental report, Microsoft disclosed that its global water consumption spiked 34% from 2021 to 2022, an increase that outside researchers tie to AI.

It is imperative to find ways to make AI processing more energy efficient and sustainable. But most reports focus almost entirely on the energy used by AI in the cloud and in data centers.

Increasing Efficiency by Running AI Models in Devices

Generative AI does not have to run exclusively in the cloud.

Currently, training a consumer-grade generative AI model requires a massive cluster of AI hardware and the power to run it. A researcher at the University of Washington estimated that training a model like ChatGPT-3 could use up to 10 gigawatt-hours, roughly equivalent to the annual energy consumption of 1,000 U.S. households.⁴

But once an AI model is trained, it can be reduced and optimized to run on a significantly less power-hungry piece of hardware, like a smartphone or battery-powered laptop.

For instance, research by analyst firm Creative Strategies⁵ concludes that Snapdragon 8 Gen 3, a flagship processor for smartphones, is 30 times more efficient than a data center on image generation tasks. For laptop PCs, the same report states that Snapdragon X Elite Compute Platform is nearly 28 times more efficient than running the AI task on the data center.

Running AI on local, private devices also saves the expense of sending queries and data across the network (and through the internal data-routing systems at a cloud provider) and sending the answers back.

Finally, the limited processing power of local devices, compared to massive resources available to run queries in cloud data centers, enforces a form of AI discipline on AI software companies, app developers and users. Not all generative AI queries require the resources of cloud-based ChatGPT-4 or its equivalent. By reallocating a portion of AI tasks to the edge, we can leverage the benefits of on-device AI processing, which offers efficient computations with minimal power consumption. A balanced strategy, involving a deliberate distribution of AI workloads across the cloud and edge, can enhance performance efficiency and minimize energy consumption.

As technology providers begin to distribute generative AI capabilities to personal devices and start to gather data on the economics of various query types and where those queries run, we expect that they will start to surface these calculations for users, allowing people to make individual cost-based decisions about how much AI processing power they consume.

Taking Efficient Edge AI Technologies to the Cloud

The technology that enables edge devices, such as smartphones and tablets, has evolved to be both powerful and power-efficient. Users expect these devices to be fast, responsive, and capable of lasting a full day on a single battery charge.

In fact, modern smartphones have surpassed the power of IBM’s Deep Blue supercomputer, which gained fame for defeating chess grandmaster Garry Kasparov in 1997.⁶ What’s even more impressive is that these powerful mobile devices consume significantly less energy than an LED light bulb.⁷

This remarkable energy efficiency is the result of decades of innovation in the field. Lean computing instruction sets have been developed to process data using fewer operations, while systems-on-chip integrate multiple components into a single chip to reduce power consumption.

Such innovations have allowed Qualcomm Technologies, Inc. to deliver record-breaking power-efficient cloud AI processing products. This showcases the significant potential of edge technologies in addressing the energy challenge associated with processing AI models in the cloud.

AI might mitigate its own efficiency problems

AI tools are well-suited to optimizing complex systems and can be used to reduce energy requirements and environmental impacts.⁸ There’s a possibility that AI tools can help offset some of the impacts of human-caused climate change. Research from the Boston Consulting Group says that, “AI can accelerate climate action by taking climate modeling to the next level, enabling new approaches to climate education, and supporting breakthroughs in climate science, climate economics, and fundamental research.”⁹

At the moment, the world is still gathering data on the environmental costs and benefits of our new AI tools. The recent COP 28 – UN Climate Change conference highlighted these data gaps to an extent. We are heartened that progress is being made and that AI can help; as Microsoft’s Brad Smith put it, “You can’t fix what you can’t measure, and these new AI and data tools will allow nations to measure emissions far better than they can today.”¹⁰

In the meantime, it’s imperative that we get a better handle on AI’s energy use itself, and do what we can to reduce that use – when possible – by running AI models on lower-power devices, and by using models that simply require less power.

The capacity of artificial intelligence to instantly assess massive volumes of data is one of its main advantages when making decisions. Both organised and unstructured data can be processed by AI algorithms from a variety of sources, including as social media, sensor networks, external market trends, and internal databases. Even in high-pressure scenarios where time is of the essence, AI systems may furnish leaders with timely and actionable insights and predictive analytics to guide their decisions through the collection and analysis of this data. 

One can identify future trends, dangers, and opportunities with AI-powered predictive analytics by using machine learning algorithms and historical data patterns. More so, as an executive, you can accurately predict market trends, client behaviour, and business results by utilising predictive models. This insight enables leaders to stay ahead of the curve by taking initiative when faced with difficult choices, anticipating problems, and seizing new possibilities. 

A major takeaway from the article for me is that in high-pressure environments, leaders often face complex and multifaceted risks that require careful assessment and mitigation strategies. What AI technologies can do in such times is to assist leaders in identifying potential risks, evaluating their impact, and devising risk management plans in real time. Machine learning algorithms can analyse historical data, identify risk factors, and predict potential outcomes, enabling leaders to make informed decisions that minimise risks and maximise rewards even in the face of uncertainty.

Leaders can improve their decision-making processes and their cognitive capacities by using AI-powered cognitive aid systems, which offer individualised decision-support tools. These systems make use of cognitive computing, machine learning, and natural language processing (NLP) to comprehend complicated inquiries, sort through large volumes of data, and offer pertinent insights and recommendations that are suited to the particular requirements of leaders. Leaders can make decisions under pressure with clarity and confidence by using these AI-driven decision support tools, which use data-driven insights to guide decisions. 

AI-driven scenario planning and simulation tools enable leaders to model different decision outcomes, evaluate alternative strategies, and assess the potential impact of their choices in simulated environments. By running “what-if” scenarios based on historical data and predictive models, leaders can gain a deeper understanding of the potential consequences of their decisions and identify optimal courses of action. This proactive approach to decision-making allows leaders to anticipate challenges, devise contingency plans, and make better-informed decisions under pressure. 

I must emphasise at this point that, even if AI technologies can be a great help in decision-making, ethical concerns and human oversight still need to be taken into account. To prevent unforeseen effects or biases in decision-making processes, leaders must guarantee that AI systems are transparent, accountable, and in line with ethical norms. In high-stress scenarios, human judgment, intuition, and morality are still crucial, and artificial intelligence (AI) should be seen as an adjunct rather than a replacement for human decision-making. 

I think there is a lot of promise in integrating AI technologies to help make better decisions under pressure. One may access actionable insights and optimize decision-making processes even in the most difficult situations by utilising real-time data analysis, predictive analytics, risk assessment, cognitive aid, scenario planning, and simulation. You can handle high-pressure circumstances with confidence, agility, and resilience when AI technologies and human judgment are combined appropriately. This can easily lead to improved outcomes for stakeholders and businesses.

Read all here…