Qualcomm’s Generative AI Leap with Adobe

Here is what’s new in the AI world.

Adobe GenStudio to Power Qualcomm’s Generative AI Content Supply Chain

Adobe today announced that Qualcomm Incorporated has selected its AI-powered solution, Adobe GenStudio, to revolutionize its content supply chain.

As Qualcomm continues to lead in intelligent computing, its marketing teams face increasing pressure to deliver vast amounts of personalized content across numerous digital channels to accelerate sales.

Adobe GenStudio will empower Qualcomm to meet this demand by using generative AI to streamline the entire content lifecycle from production and customization to activation and performance measurement.

Varun Parmar, General Manager of Adobe GenStudio and Firefly Enterprise, added, "Inefficient content supply chains often hinder personalization at scale.

Adobe GenStudio uniquely combines AI, creativity, and marketing solutions to help Qualcomm overcome these roadblocks, dramatically increasing output without sacrificing quality."

Key applications within Adobe GenStudio that Qualcomm will leverage include

This new investment builds upon Qualcomm's existing Adobe ecosystem, which includes Adobe Workfront for work management and Marketo Engage for marketing automation and customer insight.

By integrating AI across its content supply chain, Qualcomm aims to enhance its marketing agility and impact in a competitive digital landscape.

Open-Source AI Aims for Faster, Cheaper Therapies

Understanding a disease requires seeing it first. However, visualizing the molecular processes behind illnesses like novel viruses or Alzheimer's is notoriously difficult and expensive.

A new artificial intelligence tool from Virginia Tech, called ProRNA3D-single, is now bringing these invisible battles into sharp relief.

Developed by computer scientist Debswapna Bhattacharya and his team, the tool offers a more accurate way to predict and generate 3D models of how viral RNA interacts with human proteins.

This interaction is critical; it determines whether an infection spreads or a neurological disease takes hold. The ultimate goal is to accelerate drug discovery, potentially stopping pandemics before they start or halting the progression of debilitating diseases.

A "Bilingual" AI for Biology

Previous AI systems have created "alphabets" to represent biological sequences, training large language models (LLMs), similar to ChatGPT, to analyze DNA, RNA, and proteins.

ProRNA3D-single goes a step further by merging two separate LLMs (one for proteins and one for RNA) into a single system that allows them to "talk" to each other.

"This is basically a neural pairing... leading to bilingual reasoning," Bhattacharya explained. From these "conversations," the AI can generate detailed 3D images of molecular structures, a significant leap beyond the capabilities of even recent models from leaders like Google DeepMind.

From Blur to High-Definition

This breakthrough moves medical research away from costly trial-and-error experiments. For drug developers, it means they can now see precisely where a virus latches onto a human protein and design a drug to block that attachment.

"Modeling of protein-RNA interactions in 3D is crucial so that we know where a drug can actually target molecules that cause disease."

While tested on viruses, the method is universal and can be applied to any disease involving RNA-protein interactions, opening doors to treatments for a wide range of conditions.

An Open-Source Effort for Global Benefit

The product of two years of work led by dedicated Ph.D. students, the team has made its work open source.

"Taxpayers fund us, so we have an obligation to give back," Bhattacharya stated, emphasizing a commitment to open science.

Despite this significant progress, the researchers remain focused on the long road ahead.

"We should constantly remind ourselves the problem is far from being solved… these models have a long way to go," Bhattacharya noted, with the team already planning future developments to improve the tool’s accuracy and detail.

OpenAI Partners with Broadcom to Develop In-House AI Chip

A new report from Commerce and Future Commerce reveals that younger generations are spearheading the adoption of "agentic commerce," using AI platforms as primary tools for shopping and product discovery.

The study, titled ‘New Modes: How AI is Shaping New Commerce Contexts and Expectations,’ found that 33% of Gen Z and 26% of Millennials now prefer using AI for product research, compared to 37% and 40% using search engines, respectively.

This contrasts sharply with older generations, where only 13% of Gen X and 3% of Baby Boomers use AI for this purpose.

The integration of large language models (LLMs) like ChatGPT and Perplexity into daily life is becoming commonplace, with 41% of all respondents using them daily.

Their prevalence for mid-funnel activities such as comparing products and brands signals a critical shift, forcing brands to understand when and why customers turn to AI.

The report advises that brands must develop an Answer Engine Optimization (AEO) or Generative Engine Optimization (GEO) strategy. This involves supplying rich, structured product data to these AI platforms to ensure visibility and influence consumer decisions closer to the point of purchase.

Key takeaways from the report include:

The data confirms that AI platforms are no longer just tools but are becoming trusted companions in the consumer journey, reshaping shopping behaviors and redefining where brands must establish relevance and loyalty.

To thrive in this new "agentic commerce" era, brands need an intelligent data foundation that empowers these AI interactions. DataManagement.AI provides a critical advantage here.

The platform ensures that the complex data fueling these AI agents, from product information to customer insights, is accurate, governed, and seamlessly integrated.

By automating data workflows and providing AI-driven optimization, DataManagement.AI enables brands to confidently feed these platforms with the rich, structured data required for effective Answer Engine Optimization (AEO), ensuring they earn visibility and trust within the AI-driven channels where the next generation of shoppers is starting their journey.

Launch of SoftBank and OpenAI’s Japan AI Joint Venture Pushed Back

Plans by SoftBank to establish a joint venture with OpenAI, aimed at providing artificial intelligence services to Japanese businesses, are running significantly behind schedule, according to a source familiar with the matter.

The venture, originally slated to launch this summer, is taking longer than expected to prepare. An update on its progress is now anticipated in November, the unnamed source stated, as the details remain private.

When approached for comment, SoftBank confirmed that preparations are ongoing but declined to provide specifics.

OpenAI did not immediately respond to a request for comment.

The partnership, dubbed SB OpenAI Japan, was first announced in February by SoftBank CEO Masayoshi Son and OpenAI CEO Sam Altman.

The structure would involve ownership by OpenAI and a separate company established by SoftBank and its Japanese telecommunications subsidiary.

At a June shareholder meeting, the CEO of SoftBank's telecom unit, Junichi Miyakawa, had identified the end of July as the target for establishing the venture, noting that the specific products and services to be offered were still under discussion.

This initiative marks a return to high-profile investing for Son, who is once again making ambitious bets on AI after a period of retrenchment following several underperforming tech investments.

The delay is not SoftBank's only major AI project facing hurdles.

Last month, Chief Financial Officer Yoshimitsu Goto also reported that the company's ambitious $500 billion "Stargate" project, a plan to develop advanced data centers in the U.S., has been slowed down by prolonged negotiations and pending decisions on locations.

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-Shen & Towards AGI team