Google’s AlphaProof and AlphaGeometry 2 set new benchmarks in AI math-solving

Alphabet’s Google has revealed two innovative AI systems, AlphaProof and AlphaGeometry 2, which demonstrate significant advancements in solving complex mathematical problems. These systems tackled abstract math more effectively than previous AI models, showcasing enhanced reasoning capabilities.

DeepMind, Google’s AI unit, reported that these models managed to solve four out of six questions at the 2024 International Math Olympiad. AlphaProof, which integrates the Gemini language model with the AlphaZero system, solved three problems, including the most challenging one, while AlphaGeometry 2 solved another.

These achievements mark the best performance by an AI system in the competition to date, with some problems solved in minutes and others taking up to three days. Meanwhile, Microsoft-backed OpenAI is developing a similar project known as ‘Strawberry,’ raising concerns among its staff about its potential impact on humanity.

Sustainable Metal Cloud plans global expansion amid rising demand

Singapore-headquartered AI cloud provider Sustainable Metal Cloud (SMC) is set to expand globally, driven by fast-growing demand for its energy-saving technology. CEO and co-founder Tim Rosenfield announced plans to extend operations to EMEA (Europe, Middle East, and Africa) and North America in response to client demand. Currently, SMC operates “sustainable AI factories” in Australia and Singapore, with new launches planned in India and Thailand.

Partnering with AI chip giant Nvidia, SMC uses over 1,200 of Nvidia’s high-end H100 AI chips in Singapore to run open-source models like Meta’s Llama 2. Unlike most data centres that rely on air cooling technology, SMC employs immersion cooling, submerging Dell servers fitted with Nvidia GPUs in a synthetic oil called polyalphaolefin. The following method reduces energy consumption by up to 50% compared to traditional air cooling.

The International Energy Agency (IEA) anticipates a tenfold increase in AI demand compared to 2023, with global data centre electricity consumption expected to exceed 1,000 terawatt-hours by 2026. Sustainable Metal Cloud is currently raising $400 million in equity and $550 million in debt to support its expansion, according to sources. That move aligns with the increasing environmental concerns impacting Singapore’s data centre growth and highlights the importance of sustainable technology in meeting future energy demands.

Data centres surpass urban homes in Ireland’s electricity consumption

According to the Central Statistics Office, Ireland’s data centres consumed more electricity last year than all its urban homes combined. These centres used 21% of the country’s electricity, a fifth more than in 2022, surpassing the 18% used by urban homes.

Experts worry this spike could hinder climate goals in Ireland and Europe. Within the Irish tech hub, Google reported a 48% rise in emissions due to its data centres, threatening its green targets. With AI advancements, data centres could use 31% of Ireland’s electricity in three years, overtaking the 28% used by all homes.

Despite the rapid growth of data centres fueled by Ireland’s low corporate taxes, the country’s heavy reliance on fossil fuels, which supply over 50% of its electricity, poses a challenge to environmental goals. Professor Paul Deane, a senior research fellow at University College Cork, highlights the need for swift renewable energy expansion, noting that while wind accounts for 34.6% of the power, solar is only at 1.2%.

Why does it matter?

The environmental impacts of data centres are already on the European Union’s radar. The European Commission recently adopted a new regulation requiring EU data centres to report key sustainability performance indicators starting in September 2024, aiming to increase transparency, enhance energy efficiency, and support climate-neutrality actions.

Seomjae is set to launch its AI-powered mathematics learning program at CES 2025

Seomjae, a Seoul-based education solutions developer, is set to launch its AI-powered mathematics learning program at the Consumer Electronics Show in Las Vegas next January. The program uses an AI Retrieval-Augmented Generation model, developed over two years by a team of 40 mathematicians and AI developers. It features over 120,000 math problems and 30,000 lectures, offering personalised education tracks for each student.

Beta testing will begin on July 29, involving 50 students from Seoul, Ulsan, and Boston. The feedback will help enhance the technology and its feasibility. The innovative system, called Transforming Educational Content to AI, extracts and analyses information from lectures and problem solutions to provide core content.

Seomjae is also expanding its business portfolio to include an essay-writing educational program through partnerships in the US and Vietnam. The company will participate in Dubai’s Gulf Information Technology Exhibition this October, showcasing its new educational technologies.

A company official expressed excitement about starting beta testing and integrating diverse feedback to improve the program. The goal is to refine the AI system and ensure its effectiveness for students worldwide.

CMA CGM and Google join forces on AI solutions

French shipping and logistics company CMA CGM has partnered with Alphabet’s Google to accelerate the deployment of AI solutions across its global operations. The collaboration aims to boost efficiency and reduce delivery times by optimising routes, container handling, and inventory management while minimising costs and carbon emissions. CMA CGM’s Chairman and CEO Rodolphe Saadé described the partnership as a crucial step in the company’s transformation strategy.

Google France CEO Sébastien Missoffe highlighted Google’s infrastructure, data expertise, and long-term AI approach as key factors that will support CMA CGM’s growth. CEVA Logistics, CMA CGM’s logistics arm, will utilise Google’s AI-based management tools to enhance volume and demand forecasting, improving operational planning at its warehouses.

The partnership extends to CMA CGM’s media arm, which holds stakes in French private broadcaster M6 and recently acquired BFM TV. The media division aims to develop tools to help journalists synthesise and translate documents, generate media snippets for social networks, and digitise archives for research purposes. This collaboration underscores the growing trend of leveraging AI to address challenges across various industries, similar to the partnership between Airbus and Agrimetrics in agronomy.

AI boom challenges China’s renewable energy goals

Chinese tech giants Alibaba, Tencent, and Baidu have made only limited progress in meeting their renewable energy goals, according to a recent Greenpeace East Asia report. The sector’s power consumption is expected to surge due to growing demand for AI and cloud services, prompting calls for more robust action against climate change.

The report tracked the renewable energy use of top 25 cloud providers and data centre operators in China. Although Alibaba, Tencent, and Baidu led in renewable energy procurement and carbon reduction measures, significant disparities remain across the industry. Only five companies reported annual renewable energy ratios exceeding 10%, a notable increase from just one company in 2022.

Despite these advances, only eight companies have committed to 100% renewable energy use by 2030, and only six have set carbon neutrality goals for their direct and indirect emissions. Greenpeace stressed the need for the tech sector to rapidly expand renewable energy consumption to meet the projected 160% increase in power demand for data centres by 2030, driven by AI development.

AI model improves speed and accuracy of heart MRI analysis

Researchers from the Universities of East Anglia, Sheffield, and Leeds have developed an AI model to examine heart images from MRI scans. The model uses a four-chamber plane view to quickly and accurately determine the size and function of the heart’s chambers. 

Dr Pankaj Garg from UEA’s Norwich Medical School stated that while manual MRI analysis can take up to 45 minutes, the AI model performs the task in just a few seconds.

The study used data from 814 patients at Sheffield and Leeds hospitals to train the AI model, with additional testing on 101 patients from Norfolk and Norwich University Hospitals. 

Unlike previous studies, this model was trained on diverse data from multiple hospitals and scanner types, providing a comprehensive analysis of all four heart chambers. Dr Hosamadin Assadi from UEA highlighted the model’s potential to improve diagnosis, treatment decisions, and patient outcomes.

Future research will focus on testing the AI model with larger patient groups from different hospitals and scanner types. The study was a collaboration between several universities and NHS trusts, supported by the Wellcome Trust Clinical Research Career Development Fellowship.

New AI partnership focuses on early lung cancer diagnosis

Personalised medicine company Spesana and Imidex, developer of computer-aided detection technology, have announced a strategic partnership to explore AI’s impact on lung cancer detection. The collaboration will combine Imidex’s VisiRad XR detection algorithm and Spesana’s medical data platform to study the detection rates of lung nodules and masses in existing chest x-rays.

The clinical trial aims to quantify how many additional lung masses can be identified, identify at-risk patients for clinical trials, and evaluate the use of liquid biopsies resulting from nodule detection. Carla Balch, CEO of Spesana, envisions early lung cancer detection leading to earlier treatment and better patient outcomes.

Wes Bolsen, CEO of Imidex, highlighted that their FDA-cleared algorithm will improve the screening of potential lung cancer patients. The collaboration aims to equip healthcare providers and pharmaceutical companies with tools to detect lung nodules earlier, optimising healthcare resources and improving patient outcomes.

GSMA announces global effort to improve smartphone access

The GSMA has announced the formation of a global coalition to make smartphones more accessible and affordable for some of the world’s poorest populations. The coalition will include mobile operators, vendors, and significant institutions such as the World Bank Group, the United Nations’ ITU agency, and the WEF Edison Alliance.

The group aims to reduce the barriers to entering the digital economy for low-income populations, particularly in Sub-Saharan Africa and South Asia. The GSMA highlighted that handset affordability is the most significant obstacle preventing people from going online.

In many low and middle-income countries, mobile phones are often the only means of accessing the internet. Currently, 38% of the global population cannot use mobile internet due to high costs and lack of skills. The coalition will work together to improve access to affordable internet-enabled devices, aiming to close the ‘Usage Gap’ that hinders around three billion people from fully participating in the global digital economy.

AI investment risks and uncertainties highlighted by Goldman Sachs

Goldman Sachs has cast doubt on the economic viability of AI investments, despite substantial spending on AI infrastructure. The firm estimates around $1 trillion will be spent on AI-related infrastructure, including data centres, semiconductors, and grid upgrades. However, Goldman Sachs raises a crucial question: what problem will this massive AI investment actually solve?

According to Jim Covello, head of global equity research at Goldman Sachs, the current scenario contrasts sharply with past technological transitions. He argues that while the internet revolutionised commerce by offering low-cost solutions, AI today is exceedingly expensive and lacks clear applications capable of justifying its high costs. Covello highlights concerns that investor enthusiasm may wane if substantial AI use-cases fail to materialise within the next 12 to 18 months.

Despite these reservations, Kash Rangan of Goldman Sachs acknowledges that the AI cycle is still in its early stages, primarily focused on building infrastructure rather than discovering groundbreaking applications. He remains optimistic that as the AI ecosystem matures, a transformative ‘killer application’ will eventually emerge.

Looking forward, Goldman Sachs anticipates that the ongoing AI build-out will exert considerable pressure on national grids and electricity consumption. The report forecasts a 2.4% compound annual growth rate in UK electricity demand and projects that data centres will double their electricity consumption by 2030, underscoring the immediate impacts of AI infrastructure development on energy resources.

While AI holds potential for revolutionary advancements, Goldman Sachs suggests that its current trajectory raises fundamental questions about economic feasibility and the pace of transformative breakthroughs needed to justify its substantial investments.