Tools & Platforms

check out this week’s coolest retail technology plays — Retail Technology Innovation Hub

Published

1 week ago

September 5, 2025

Central Co-op, Lincolnshire, Midcounties co-operatives

SymphonyAI reports that Central Co-op, Lincolnshire, and Midcounties co-operatives have deployed its Connected Retail platform in a bid to modernise operations, localise assortments, and enhance the member experience across more than 700 stores serving over 1.3 million shoppers.

Using generative and predictive AI, this delivers real-time intelligence across inventory management, shelf execution, and supply chain operations.

“With SymphonyAI’s range and space planning, we can quickly adjust our assortments to meet changing member shopper preferences while automating labour intensive tasks to allow our teams to focus on delivering exceptional service,” says Jacob Isherwood, CIO, Midcounties Co-op.

“Our priority is to keep shelves stocked with the right products, reduce waste, and minimise overhead costs. With SymphonyAI’s platform, we’re able to enhance our operational efficiency and meet the evolving needs of our shoppers,” says Steve Leach, COO, Lincolnshire Co-op.

Merchmix

Merchmix has unveiled what is pitched as the world’s first agentic SaaS retail platform – a solution that, the company says, doesn’t just analyse retail data, but uses AI to ingest 200+ external sources, and delivers agentic workflows to act on it.

By autonomously optimising stock levels, sending supplier alerts, raising purchase orders, or reconfiguring in-store layouts in real-time, Merchmix claims to eliminate one of retail’s most costly inefficiencies: stock optimisation.

It unites planning, buying, merchandising, and store operations in one platform. Retailers can ask: “Which SKUs will sell out in Manchester this weekend?” or “What if I move 10% of stock online?” – and Merchmix delivers both the analysis and takes action with autonomous agentic workflows.

“Launching new international markets at Marks & Spencer taught me every customer base in each country behaves differently, and those nuances are expensive to get wrong,” says Nicola Bond, Co-Founder and CEO at Merchmix who has 18 years expertise spanning retail and tech including senior buying roles at Asos, Debenhams and Best and Less.

“We’ve built the colleague every retailer wishes they had – one who never sleeps, knows the data inside-out, and helps you make the right call to protect margin and growth whether you’re a buyer, merchandiser, or store manager.”

AiFi and Miami Freedom Park

AiFi is working with Miami Freedom Park, a 25,000-seat soccer specific stadium currently under construction in Miami, Florida.

It is planned to be the home of Major League Soccer club Inter Miami CF. In 2022, final approval was given by the City of Miami to build a stadium on the current site of the Melreese golfcourse, close to Miami International Airport. This is set to open for the 2026 MLS season.

In a LinkedIn post, Richard Wallace, Head of Sales and Partnerships, Americas at AiFi, said: “Big news from the sunshine state. AiFi has been selected to provide frictionless commerce at Miami Freedom Park so fans can experience faster, more seamless ordering at concessions when the stadium opens next year.”

“Stoked to see this come to life over the coming months and expand our footprint in Major League Soccer.”

Suntop

Coro’s fruit juice brand Suntop, in partnership with Appetite Creative, has launched a new connected packaging experience to kick off the back to school season with prizes and rewards for its new ‘Mega Back to School 2025’ campaign.

This aims to develop a fun, engaging instant win experience that drives sales and expands Suntop’s reach to include Gen Z consumers. The promotion, in partnership with the anime One Piece, is a show about pirates featuring the main character named Luffy.

Customers who get Suntop products, can scan the QR code on the packaging and register with their information to instantly enter the draw for prizes. These include trips to Japan, PlayStation 5, tablets and Funko Pops for One Piece characters, plus digital wallpapers that everyone wins upon completing their entries.

“We wanted to develop a fun, engaging and secure instant win experience that drives sales and expands Suntop’s reach to Gen Z. As society increasingly embraces technology, it’s crucial to tailor marketing strategies to align with consumer preferences, maximising the potential for impactful results. Our new back to school connected packaging campaign delivers this business goal perfectly,” says Omar Shehata, Brand Manager at Suntop.

Asos

TrusTrace has announced a partnership with Asos that aims to enhance the fast fashion online retailer’s supply chain transparency and resilience, strengthen risk management, and support compliance across its global value chain.

As part of its Fashion with Integrity strategy, Asos says it is investing in robust traceability infrastructure to gain real-time visibility into its supply chain, down to farm level (Tier 5).

By integrating TrusTrace’s AI enhanced platform, it is looking to streamline operations across risk, compliance, and impact management, ensuring timely access to trusted data that enables proactive decision-making, due diligence and compliance.

“Our partnership with TrusTrace is a key milestone in our updated Fashion with Integrity programme,” says Elena Martínez Ortiz, EVP of Product at Asos. “TrusTrace enables us to improve product traceability, helping us meet compliance standards, understand and address risks, and boost resilience in our supply chain by supporting our suppliers to implement improvements.”

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Tools & Platforms

Jared Kushner launches AI startup with top Israeli tech entrepreneur

Published

43 minutes ago

September 14, 2025

Raphael Kahan

Coming to light after operating secretly since 2024, the company raised $30 million in a Series A round led by Kushner’s Affinity Partners and Gil’s Gil Capital, with backing from prominent investors like Coinbase CEO Brian Armstrong, Stripe founder Patrick Collison and LinkedIn co-founder Reid Hoffman. Brain Co. aims to bridge the gap between large language models like GPT-5 and their practical application in organizations.

The venture began in February 2024 when Kushner, Gil, and former Mexican Foreign Minister Luis Videgaray met to address challenges large organizations face in integrating AI tools. Kushner, seeking to expand Affinity’s AI investments, connected with Gil, a former Google and Twitter executive turned venture capitalist, through his brother, Josh Kushner.

Videgaray, who met Kushner during Trump’s 2016 campaign, also joined. Brain Co. has secured deals with major clients like Sotheby’s, owned by Israeli-French businessman Patrick Drahi and Warburg Pincus, alongside government agencies, energy firms, healthcare systems and hospitality chains.

With 40 employees, Brain Co. collaborates with OpenAI to develop tailored applications. A recent MIT study cited by Forbes found that 95% of generative AI pilot programs failed in surveyed organizations, highlighting the gap Brain Co. targets.

CEO Clemens Mewald, a former AI expert at Google and Databricks, explained, “So far, we haven’t seen a reason to only double down on one sector. Actually, it turns out that at the technology level and the AI capability level, a lot of the use cases look very similar.”

He noted similarities between processing building permits and insurance claims, both requiring document analysis and rule-based recommendations, areas where Brain Co. is active.

Kushner, who founded Affinity Partners after leaving the White House, said, We’re living through a once-in-a-generation platform shift,” Kushner said in a press release. “After speaking with Elad, we realized we could build a bridge between Silicon Valley’s best AI talent and the world’s most important institutions to drive global impact.”

Affinity manages over $4.8 billion, primarily from Saudi, Qatari and UAE funds. In September 2024, Brain Co. acquired Serene AI, bringing in experienced founders. While Kushner will serve as an active board member, Gil said he will primarily operate through Affinity.

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How Alibaba builds its most efficient AI model to date

Published

48 minutes ago

September 14, 2025

The Editors

A technical innovation has allowed Alibaba Group Holding, one of the leading players in China’s artificial intelligence boom, to develop a new generation of foundation models that match the strong performance of larger predecessors while being significantly smaller and more cost efficient.

Alibaba Cloud, the AI and cloud computing division of Alibaba, unveiled on Friday a new generation of large language models that it said heralded “the future of efficient LLMs”. The new models are nearly 13 times smaller than the company’s largest AI model, released just a week earlier.

Despite its compact size, Qwen3-Next-80B-A3B is among Alibaba’s best models to date, according to developers. The key lies in its efficiency: the model is said to perform 10 times faster in some tasks than the preceding Qwen3-32B released in April, while achieving a 90 per cent reduction in training costs.

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Emad Mostaque, co-founder of the UK-based start-up Stability AI, said on X that Alibaba’s new model outperformed “pretty much any model from last year” despite an estimated training cost of less than US$500,000.

For comparison, training Google’s Gemini Ultra, released in February 2024, cost an estimated US$191 million, according to Stanford University’s AI Index.

Alibaba says its new generation of AI foundation models heralds the “the future of efficient LLMs”. Photo: Handout alt=Alibaba says its new generation of AI foundation models heralds the “the future of efficient LLMs”. Photo: Handout>

Artificial Analysis, a leading AI benchmarking firm, said Qwen3-Next-80B-A3B surpassed the latest versions of both DeepSeek R1 and Alibaba-backed start-up Moonshot AI’s Kimi-K2. Alibaba owns the South China Morning Post.

Several AI researchers attributed the success of Alibaba’s new model to a relatively new technique called “hybrid attention”.

Existing models face diminishing returns on efficiency as input lengths increase because of the way AI models determine which inputs are the most relevant. This “attention” mechanism involves trade-offs: better attention accuracy leads to higher computational expenses.

Those costs compound when models handle long context inputs, making it expensive to train sophisticated AI agents that autonomously execute tasks for users.

Qwen3-Next-80B-A3B addresses this challenge by incorporating a technique known as “Gated DeltaNet”, first proposed by researchers at the Massachusetts Institute of Technology and Nvidia in March.

Gated DeltaNet enhanced the model’s attention by making targeted adjustments to the input data and determining what information to retain and what to discard, said Zhou Peilin, an AI researcher at the Hong Kong University of Science and Technology.

This results in an accurate yet cost-effective attention mechanism. Citing scores from the Ruler benchmark, which evaluates AI models based on their ability to manage varying input lengths, Alibaba said Qwen3-Next-80B-A3B was comparable to its most powerful model, the Qwen3-235B-A22B-Thinking-2507, despite being smaller and more affordable.

Alibaba uses a technique known as “Gated DeltaNet” to develop its latest AI models. Photo: Handout alt=Alibaba uses a technique known as “Gated DeltaNet” to develop its latest AI models. Photo: Handout>

“It’s great to see that our DeltaNets … have been greatly scaled up by Alibaba to build excellent AI models,” said Juergen Schmidhuber, computer science professor at the King Abdullah University of Science and Technology, who contributed to the development of DeltaNets in the 1990s.

Qwen3-Next-80B-A3B also uses the “mixture-of-experts” (MoE) architecture, which has driven many efficiency gains in Chinese AI models over the past year, including DeepSeek-V3 and Moonshot’s Kimi-K2.

The MoE architecture divides a model into separate sub-networks or “experts” that specialise in subsets of input data to collaboratively perform tasks.

Alibaba enhanced the “sparsity” of its latest MoE architecture to improve efficiency. While DeepSeek-V3 and Kimi-K2 employ 256 and 384 experts, respectively, Qwen3-Next-80B-A3B features 512 experts but activates only 10 at a time.

According to Artificial Analysis, those innovations helped the model achieve parity with DeepSeek-V3.1, despite having just 3 billion active parameters compared with the latter’s 37 billion. Generally, a higher number of parameters indicates a more powerful model, but it also increases training and operational costs.

The efficiency gains are evident on Alibaba’s cloud platform, where the new model costs less to run than the Qwen3-235B-2507, which contains 235 billion parameters.

The new model architecture reflects a growing interest in smaller but more efficient AI models, amid rising concerns about the costs associated with scaling up the industry’s largest models.

According to AI research firm Epoch AI, the most expensive training run to date was xAI’s Grok 4, which cost US$490 million, with future training runs expected to exceed US$1 billion by 2027.

In August, researchers at Nvidia published a paper advocating for small language models as the future of agentic AI because of their flexibility and efficiency. The company is also experimenting with the Gated DeltaNet technique on its Nemotron models.

Meanwhile, Chinese AI giants are pushing for broader adoption of their models by ensuring they are small enough to run on laptops and smartphones.

Last month, Tencent Holdings launched four open-source AI models, each under 7 billion parameters, while Beijing-based start-up Z.ai released the GLM 4.5 Air model with just 12 billion active parameters.

Alibaba’s Qwen3-Next-80B-A3B is now compact enough to operate on a single Nvidia H200 graphics processing unit, according to Artificial Analysis. On the open-source developer platform Hugging Face, the model quickly broke into the trending leaderboard, amassing almost 20,000 downloads within 24 hours after launch.

Alibaba said its new architecture served as a preview of its next generation of AI models. The future of large language models would likely revolve around refining Alibaba’s approach to address training costs and efficiency, even if entirely different architectures emerge, said Tobias Schroder, an AI researcher at Imperial College London.

This article originally appeared in the South China Morning Post (SCMP), the most authoritative voice reporting on China and Asia for more than a century. For more SCMP stories, please explore the SCMP app or visit the SCMP’s Facebook and Twitter pages. Copyright © 2025 South China Morning Post Publishers Ltd. All rights reserved.

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Google AI Chief Stresses Continuous Learning for Fast-Changing AI Era

Published

1 hour ago

September 14, 2025

Irfan Ahmad

At an open-air summit in Athens, Demis Hassabis, head of Google’s DeepMind and Nobel chemistry laureate, argued that the skill most needed in the years ahead will be the ability to keep learning. He described education as moving into a period where adaptability matters more than fixed knowledge, because the speed of artificial intelligence research is shortening the lifespan of expertise.

Hassabis said future workers will have to treat learning as a constant process, not a stage that ends with graduation. He pointed to rapid advances in computing and biology as examples of how quickly fields now change once AI tools enter the picture.

Outlook on technology

The DeepMind chief warned that artificial general intelligence may not be far away. In his view, it could emerge within a decade, carrying a weight of opportunity and risk. He described its potential impact as larger and faster than the industrial revolution, a shift that could deliver breakthroughs in medicine, clean energy, and space exploration.

Even so, he stressed that powerful models must be tested carefully before being widely deployed. The practice of pushing products out quickly, common in earlier technology waves, should not guide the release of systems capable of influencing economies and societies on a global scale.

Prime minister’s caution

Greek Prime Minister Kyriakos Mitsotakis, who shared the stage at the Odeon of Herodes Atticus, said governments will struggle to keep pace with corporate growth unless they adopt a more active role. He warned that when the benefits of technology are concentrated among a small set of companies, public confidence erodes. He tied the issue to social stability, saying communities won’t support AI unless they see its value in everyday life.

Mitsotakis pointed to Greece’s efforts to build an “AI factory” around a new supercomputer in Lavrio. He presented the project as part of a wider European push to turn regulation and research into competitive advantages, while reducing reliance on U.S. and Chinese platforms.

Education and jobs

Both speakers returned repeatedly to the theme of skills. Hassabis said that in addition to traditional training in science and mathematics, students should learn how to monitor their own progress and adjust their methods. He argued that the most valuable opportunities often appear where two fields overlap, and that AI can serve as a tutor to help learners explore those connections.

Mitsotakis said the challenge for governments is to match school systems with shifting labor markets. He noted that Greece is mainly a service economy, which may delay some of the disruption already visible in manufacturing-heavy nations. But he cautioned that job losses are unavoidable, including in sectors long thought resistant to automation.

Strains on democracy

The prime minister voiced concern that misinformation powered by AI could undermine elections. He mentioned deepfakes as a direct threat to public trust and said Europe may need stricter rules on content distribution. He also highlighted risks to mental health among teenagers exposed to endless scrolling and algorithm-driven feeds.

Hassabis agreed that lessons from social media should inform current choices. He suggested AI might help by filtering information in ways that broaden debate instead of narrowing it. He described a future where personal assistants act in the interest of individual users, steering them toward content that supports healthier dialogue.

The question of abundance

Discussion also touched on the idea that AI could usher in an era of radical abundance. Hassabis said research in protein science, energy, and material design already shows how quickly knowledge is expanding. He argued that the technology could open access to vast resources, but he added that how wealth is shared will depend on governments and economic policy, not algorithms.

Mitsotakis drew parallels with earlier industrial shifts, warning that if productivity gains are captured only by large firms, pension systems and social programs will face heavy strain. He said policymakers must prepare for a period of disruption that could arrive faster than many expect.

Greece’s role

The Athens event also highlighted the country’s ambition to build a regional hub for technology. Mitsotakis praised the growth of local startups and said incentives, venture capital, and government adoption of AI in public services would be central to maintaining momentum.

Hassabis, whose family has roots in Cyprus, said Europe needs to remain at the frontier of AI research if it wants influence in setting ethical and technical standards. He called Greece’s combination of history and new infrastructure a symbolic setting for conversations on the future of technology.

Preparing for the next era

The dialogue closed on a shared message: societies will need citizens who can adapt and learn throughout their lives. For Hassabis, this adaptability is the foundation for navigating a future shaped by artificial intelligence. For Mitsotakis, the task is making sure those changes strengthen democratic values rather than weaken them.

Notes: This post was edited/created using GenAI tools.

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