Amazon Takes Lead in AI Assistant Race As Alexa+ Hits 1M

Here is what’s new in the AI world.

1 Million Homes Now Smarter With Amazon's GenAI Alexa+

Amazon has significantly expanded its early access program for Alexa+, the generative AI-powered upgrade to its digital assistant, now reaching over one million users, according to company statements to TechCrunch. While still not publicly available, the tech giant has been systematically inviting waitlisted customers to test the enhanced service in recent weeks.

Key Features of Alexa+

Pricing & Availability

• Currently free during early access

• Post-launch: Free for Prime members, $19.99/month for others

• Initially limited to Echo Show devices (8, 10, 15, 21 models) in the U.S.

• Planned expansion to Fire TV/tablet users and additional markets

The launch represents Amazon's strategic push to revitalize its voice assistant platform, which faced declining relevance amid the generative AI boom. While Alexa devices have sold 600 million units globally, the service previously struggled to monetize its ecosystem effectively.

Early user feedback indicates promising capabilities but also highlights areas needing refinement before full launch approximately 90% of announced features are now operational, according to Amazon.

This development follows CEO Andy Jassy's May 2025 disclosure of 100,000 early users, showing rapid recent growth in the testing program. The company aims to position Alexa+ as a comprehensive AI assistant that blends conversational AI with practical task automation across smart home, entertainment, and commerce verticals.

Apple Exec Says AI Is the Goal for Chip Design, Yet It’s Already Reality

On Thursday, headlines emerged suggesting Apple is planning to use generative AI to design the chips powering its devices. These claims trace back to a speech made in May by Johny Srouji, Apple’s Senior Vice President of Hardware Technologies, during an event held by Imec, a renowned tech research institute.

In his talk, a video of which was later obtained by AppleInsider after a request to Imec Srouji, traced Apple’s journey in developing custom silicon, starting with the A4 chip and continuing up to the current M4 processor line.

While some interpreted his remarks to mean Apple is preparing to adopt AI in chip design for the first time, the reality is quite the opposite: Apple has already been using AI-driven tools in chip design for many years.

The Setting and the Real Message

Srouji received an innovation award at the ITF World conference in Antwerp, Belgium, hosted by Imec. While his speech was initially intended just for attendees, Imec later granted permission to share it more broadly.

In the speech, Srouji emphasized the importance of leveraging the latest technologies throughout Apple’s chip development process. One of the most crucial tools has been electronic design automation (EDA) software, which is developed by specialized EDA companies.

"EDA companies are super critical in supporting our chip design complexities," Srouji stated. He added that "Generative AI techniques have a high potential in getting more design work in less time, and it can be a huge productivity boost."

This combination of comments led some to conclude that Apple is only now turning to AI for chip design. But in reality, Apple has been integrating AI tools into its chip development workflow for years, particularly through the use of advanced EDA software.

How Apple Really Designs Chips

A common misconception around chip development is that Apple engineers manually design every component. In reality, while engineers do handle high-level design, such as setting specifications and overall architecture, the actual circuit-level design and layout are handled by EDA software.

This software automates the intricate details, including mapping out billions of transistors and running simulations to test performance and resolve errors.

Take the M4 chip, for instance. It contains 28 billion transistors built on a 3-nanometer process. Designing such a chip entirely by hand would be impractical and time-consuming.

That’s where AI-enhanced automation comes in. EDA tools, already embedded with machine learning, handle the bulk of these tasks. This has been standard practice at Apple for quite some time.

What’s Next: Generative AI in EDA

While Apple already uses AI in chip development, the shift now is toward generative AI, which adds a new layer of intelligence. Companies like Synopsys, one of the top EDA tool providers, are advancing the role of AI by enabling software to create novel chip designs, such as innovative ways to reduce power consumption or improve efficiency, which even experienced engineers might not consider.

For Apple, a company that thrives on pushing technological boundaries, this kind of enhancement represents an opportunity to further optimize its chips, reduce development timelines, and boost performance.

No AI Takeover, Just Smarter Tools

Some media coverage may have stirred fears about AI replacing engineers or drastically altering Apple's design teams. But that’s not the case here. Apple’s use of AI, including generative models, is meant to complement human expertise, not replace it.

The growing complexity of chip design means that AI tools are no longer optional; they’re essential. Apple’s approach isn’t new, nor is it disruptive to its existing teams. Instead, it's a continuation of its long-standing strategy: using the best available tools to build world-class chips.

Generative AI isn’t a revolutionary step for Apple; it’s the next logical evolution of systems it already has in place.

Banks and Tech Giants Unite To Develop Open-Source AI Standards

A coalition of top banks and tech companies has come together to develop standardized open-source controls for AI use in the financial sector.

Spearheaded by the Fintech Open Source Foundation (FINOS), the initiative includes major financial players like Citi, BMO, RBC, and Morgan Stanley, alongside cloud giants such as Microsoft, Google Cloud, and Amazon Web Services.

The collaboration, called the Common Controls for AI Services project, aims to create neutral, industry-wide standards that guide the responsible use of AI in finance.

This framework will be designed to align with existing regulatory requirements, providing peer-reviewed governance structures and live validation tools to help firms maintain compliance in real time. It builds on FINOS’s earlier Common Cloud Controls initiative, which was originally driven by contributions from Citi.

FINOS Executive Director Gabriele Columbro highlighted the importance of this effort, calling it a pivotal moment for AI in financial services.

He stressed that open-source collaboration allows financial institutions and third-party tech providers to work together early on shared goals like security and compliance.

Rather than developing siloed standards, the project encourages a unified strategy that can reduce inconsistencies across different regulated regions.

The initiative is open to contributions from additional financial firms, AI developers, regulators, and tech providers.

Operating under the Linux Foundation, FINOS offers a neutral platform where competitors can jointly build tools that ensure AI in finance is safe, transparent, and efficient.

Linux Foundation Flags AI Talent Shortage and Rise in Open Source Use

The Linux Foundation, in partnership with LF Research and Linux Foundation Education, has released its 2025 State of Tech Talent report, shedding light on the growing impact of AI on the tech workforce and the critical need for upskilling and open-source adoption.

Drawing on insights from over 500 global hiring and training leaders, the report reveals a sharp rise in the demand for AI expertise, while highlighting a gap in workforce readiness to meet this shift.

AI is rapidly reshaping business operations, with 94% of organizations expecting it to deliver significant value. However, fewer than half currently possess the core AI capabilities needed to fully harness its potential.

Key challenges include

AI is also changing how teams function. Two-thirds of organizations report significant workflow changes, with developers now needing to validate AI-generated code, new hires expected to bring AI proficiency, and many entry-level responsibilities being automated.

Upskilling Becomes the Strategic Focus

In response to the shifting demands, organizations are prioritizing internal talent development:

• 72% now focus on upskilling existing staff, a notable jump from 48% in 2024.

• Upskilling is 62% faster than hiring and 91% more effective at improving employee retention.

• 71% of employers value certifications as proof of technical competence.

• 56% of companies prefer upskilling over external hiring or contracting to bridge their AI/ML skills gap.

Open Source Fuels AI Growth and Retention

Open source plays a vital role in AI adoption, with 40% of organizations using open source frameworks, models, and tools to speed up implementation. These practices not only accelerate innovation but also boost employee engagement and retention:

• 91% of companies say technical training supports retention.

• 84% report that fostering an open-source culture helps keep talent.

• Research from the Linux Foundation and Meta shows open-source collaboration fosters faster, higher-quality AI development through cross-organizational partnerships.

Leaders Weigh In: Training Is the New Competitive Edge

Clyde Seepersad, SVP and GM of Linux Foundation Education, stressed that the success of AI initiatives relies not just on tools, but on teams that are trained to use them.

He cited a BCG study showing that 70% of AI transformation success depends on people and processes, noting that upskilling must be treated as a fundamental business capability.

Frank Nagle, Advising Chief Economist at the Linux Foundation, added that the rise of AI demands not just new technology but a major shift in human capital.

He emphasized that AI success is less about acquiring tools and more about building the workforce to use them, urging companies to invest in internal talent to stay competitive.

OpenAI CEO Sam Altman Hints at Future Ads In ChatGPT

Sam Altman, CEO of OpenAI, has given his most direct remarks to date on the possibility of introducing advertising into ChatGPT, suggesting the company is now more open to the idea as it navigates rising financial demands and gears up for its next major product launch.

In the first episode of OpenAI’s new official podcast, Altman confirmed that while ChatGPT currently has no ad product, advertising is actively being explored. “I’m not totally against it,” he said, adding that he appreciates well-designed ads, such as those on Instagram, which have influenced some of his own purchases. However, he emphasized that any ad implementation would need to be done with great care.

This marks a shift from Altman’s previous stance. During a 2024 talk at Harvard Business School, he called advertising a "last resort" and something he hoped to avoid.

But with OpenAI now reportedly spending between $3 and $4 billion annually to operate ChatGPT and projecting $12.7 billion in revenue for 2025, the urgency to diversify revenue streams is growing.

To date, OpenAI has largely relied on substantial venture funding, including a massive $40 billion round earlier this year and ongoing backing from tech giants like Microsoft and Nvidia.

The company also recently signed a $200 million contract with the U.S. Department of Defense. Despite these funding sources, as AI becomes more embedded in everyday life, sustainable monetization is becoming more important.

A core concern for Altman is preserving user trust. While he sees value in well-placed ads, he was clear that OpenAI would not compromise the integrity of ChatGPT’s responses for money. “If we started modifying the output... based on who pays us more, that would feel really bad,” Altman said. “I think that’d be like a trust-destroying moment.”

Instead, he suggested alternative models, such as affiliate links or transaction-based approaches that don’t interfere with the chatbot’s answers. Another idea is placing ads in non-intrusive areas like sidebars or footers, so the core user experience remains unaffected.

As other AI platforms like Google’s Gemini begin testing ads within AI-generated content, the pressure to monetize is mounting. Still, OpenAI appears committed to moving forward thoughtfully.

While there's no set timeline for introducing ads into ChatGPT, it's now clear that the company is considering the possibility. The real question ahead isn't if ads will appear, but how they’ll be integrated, and whether it can be done without undermining user trust.

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-Shen & Towards AGI team