Sony-Backed AI Licensing Startup Vermillio Secures $16 Million in Series A Funding - Related to have, million, new, gemini, startup
Free Gemini users just got a big upgrade, plus paid users have a new Live perk
As part of its ongoing quest to continue upgrading its AI, Google is making some changes to Gemini -- making a paid feature free to everyone and giving Gemini the ability to see the world around it.
Gemini gets a memory upgrade for all clients.
First up, the ability for Gemini to remember your preferences, interests. Work, and more is coming to all people. This feature debuted last November as a Gemini Advanced exclusive (and, for comparison, has existed on ChatGPT for a while).
Also: Google's Gemini AI might soon back up Siri on your iPhone - just like ChatGPT.
Saved info lets you tell Gemini certain details about your life, like your name. Your family's name, or a specific project you're using ChatGPT for. This means you won't have to enter this information each time, and you'll get more relevant answers.
Google offered a few more suggestions for the feature, including:
I'm vegetarian, so don't suggest recipes with meat.
After responding. Include a Spanish translation.
When trip planning, include the cost per day.
You will need to add each piece of saved info manually. To do so, head to the settings menu and find "Saved info." The feature does appear to be rolling out on the desktop version first, but it's headed to both desktop and. The mobile app.
In addition, at last week's Mobile World Congress, Google showcased that Gemini Live can now "see" -- either from your screen or from a live video. This feature, which will be rolling out later this month, is only available to paid Gemini Advanced consumers for now.
With this feature. You'll see a "Share screen with Live" button when you open Gemini. Tap it, and you'll have the option to share your screen or start a video. You can ask the AI questions about your surroundings or about what's on your phone screen.
Also: Gemini Live just got much easier to talk to - here's how.
In a demo video. A user asks for outfit ideas using a pair of pants shown on screen. Gemini recommends a top, and the user then asks for a jacket recommendation. In another showcasing live video, a user asks Gemini for help picking a glaze color for a vase they just created. Gemini ends up picking "the first one on the left in the second row" when shown a display of available options—fairly impressive context.
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Opera is now the first major web browser with AI-based agentic browsing
The team behind the Opera web browser has introduced a new AI agent called Browser Operator, capable of performing browsing tasks for clients. This new agentic browsing marks a paradigm shift that could mark the next evolution of web browsers.
Also: Which AI agent is the best? This new leaderboard can tell you.
, EVP at Opera, "For more than 30 years, the browser gave you access to the web. But it has never been able to get stuff done for you. Now it can. This is different from anything we've seen or shipped so far." Kolondra continues, "The Browser Operator we're presenting today marks the first step toward shifting the role of the browser from a display engine to an application that is agentic and performs tasks for its clients."
Via the AI agentics. The Browser Operator is designed to give the user a major efficiency boost. This is accomplished by allowing the user to explain what they need to do in natural language, and the browser will then perform the necessary tasks.
Also: Crawl, then walk, before you run with AI agents. Experts recommend.
For example, you could ask Browser Operator to buy you a pair of pink running shoes from Nike in a size The Browser Operator will then perform the task. As Browser Operator performs the task, the user can see what's happening at any point in the process, so they are in control the whole time.
Essentially, Opera is turning the browser into more of a user-focused ecosystem that uses native client-side solutions to complete tasks while protecting user privacy.
Also: How businesses are accelerating time to agentic AI value.
Building on these developments, the Browser Operator runs natively inside the browser and uses the DOM Tree and. Browser layout data to get context. , that makes the solution faster because the browser doesn't need to "see" and. Understand what's on the screen from its pixels or navigate with a mouse pointer. Browser Operator can access an entire page at once, without the need to scroll, which means it reduces overhead and time required. And because it all happens natively within the browser, the Browser Operator doesn't require a virtual machine or cloud server.
Browser Operator is currently in feature preview status and. Should become available soon as part of the Opera Feature Drop program. I checked my up-to-date version of Opera Developer, and it has yet to hit, but I'll keep my eyes open and. Write up a how-to as soon as it's available.
You can watch Browser Operator in action on the official Opera YouTube channel. Expect Browser Operator to appear in a Feature Drop in the near future.
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Sony-Backed AI Licensing Startup Vermillio Secures $16 Million in Series A Funding
Vermillio, an AI licensing and protection platform, has successfully closed a $16 million Series A funding round, led by Sony Music Entertainment and DNS Capital.
Additionally, this investment will enable Vermillio to scale its operations and advance its technology, aimed at safeguarding and monetising creative content in the ever-evolving generative AI landscape.
At the heart of Vermillio’s innovation is TraceID, a technology designed to provide secure licensing, attribution, and compensation for intellectual property in the age of AI.
Dan Neely, co-founder & CEO of Vermillio, emphasises the platform’s mission to establish a new standard for AI licensing. Ensuring that consent, credit, and compensation are prioritised.
“With the support of an innovation leader like Sony Music, Vermillio will continue building our products to ensure generative AI is utilised ethically and securely. At this critical moment in determining the future of AI and how to hold platforms accountable, we are proud to protect the world’s most beloved content and talent,” Neely stated.
“Sony Music is focused on developing responsible generative AI use cases that enhance the creativity and goals of our talent, protect their work, excite fans, and. Create new commercial possibilities,” mentioned Dennis Kooker, president, global digital business, Sony Music Entertainment.
Vermillio mentioned its practical applications in collaborations with major industry players. For instance, the successful launch of a Spider-Verse AI engine with Sony Pictures, where fans created personalised digital avatars, showcased the use-case of TraceID in maintaining IP integrity while enabling fan engagement.
The technology’s ability to track and attribute content is also seen in projects with The Orb and David Gilmour of Pink Floyd, which allowed fans to remix their album.
With this new funding. Vermillio is set to expand its reach and solidify its position as a leader in AI rights management, ensuring that the AI copyright battles will not be a waste of time.
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Market Impact Analysis
Market Growth Trend
| 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 |
|---|---|---|---|---|---|---|
| 23.1% | 27.8% | 29.2% | 32.4% | 34.2% | 35.2% | 35.6% |
Quarterly Growth Rate
| Q1 2024 | Q2 2024 | Q3 2024 | Q4 2024 |
|---|---|---|---|
| 32.5% | 34.8% | 36.2% | 35.6% |
Market Segments and Growth Drivers
| Segment | Market Share | Growth Rate |
|---|---|---|
| Machine Learning | 29% | 38.4% |
| Computer Vision | 18% | 35.7% |
| Natural Language Processing | 24% | 41.5% |
| Robotics | 15% | 22.3% |
| Other AI Technologies | 14% | 31.8% |
Technology Maturity Curve
Different technologies within the ecosystem are at varying stages of maturity:
Competitive Landscape Analysis
| Company | Market Share |
|---|---|
| Google AI | 18.3% |
| Microsoft AI | 15.7% |
| IBM Watson | 11.2% |
| Amazon AI | 9.8% |
| OpenAI | 8.4% |
Future Outlook and Predictions
The Users Free Gemini landscape is evolving rapidly, driven by technological advancements, changing threat vectors, and shifting business requirements. Based on current trends and expert analyses, we can anticipate several significant developments across different time horizons:
Year-by-Year Technology Evolution
Based on current trajectory and expert analyses, we can project the following development timeline:
Technology Maturity Curve
Different technologies within the ecosystem are at varying stages of maturity, influencing adoption timelines and investment priorities:
Innovation Trigger
- Generative AI for specialized domains
- Blockchain for supply chain verification
Peak of Inflated Expectations
- Digital twins for business processes
- Quantum-resistant cryptography
Trough of Disillusionment
- Consumer AR/VR applications
- General-purpose blockchain
Slope of Enlightenment
- AI-driven analytics
- Edge computing
Plateau of Productivity
- Cloud infrastructure
- Mobile applications
Technology Evolution Timeline
- Improved generative models
- specialized AI applications
- AI-human collaboration systems
- multimodal AI platforms
- General AI capabilities
- AI-driven scientific breakthroughs
Expert Perspectives
Leading experts in the ai tech sector provide diverse perspectives on how the landscape will evolve over the coming years:
"The next frontier is AI systems that can reason across modalities and domains with minimal human guidance."
— AI Researcher
"Organizations that develop effective AI governance frameworks will gain competitive advantage."
— Industry Analyst
"The AI talent gap remains a critical barrier to implementation for most enterprises."
— Chief AI Officer
Areas of Expert Consensus
- Acceleration of Innovation: The pace of technological evolution will continue to increase
- Practical Integration: Focus will shift from proof-of-concept to operational deployment
- Human-Technology Partnership: Most effective implementations will optimize human-machine collaboration
- Regulatory Influence: Regulatory frameworks will increasingly shape technology development
Short-Term Outlook (1-2 Years)
In the immediate future, organizations will focus on implementing and optimizing currently available technologies to address pressing ai tech challenges:
- Improved generative models
- specialized AI applications
- enhanced AI ethics frameworks
These developments will be characterized by incremental improvements to existing frameworks rather than revolutionary changes, with emphasis on practical deployment and measurable outcomes.
Mid-Term Outlook (3-5 Years)
As technologies mature and organizations adapt, more substantial transformations will emerge in how security is approached and implemented:
- AI-human collaboration systems
- multimodal AI platforms
- democratized AI development
This period will see significant changes in security architecture and operational models, with increasing automation and integration between previously siloed security functions. Organizations will shift from reactive to proactive security postures.
Long-Term Outlook (5+ Years)
Looking further ahead, more fundamental shifts will reshape how cybersecurity is conceptualized and implemented across digital ecosystems:
- General AI capabilities
- AI-driven scientific breakthroughs
- new computing paradigms
These long-term developments will likely require significant technical breakthroughs, new regulatory frameworks, and evolution in how organizations approach security as a fundamental business function rather than a technical discipline.
Key Risk Factors and Uncertainties
Several critical factors could significantly impact the trajectory of ai tech evolution:
Organizations should monitor these factors closely and develop contingency strategies to mitigate potential negative impacts on technology implementation timelines.
Alternative Future Scenarios
The evolution of technology can follow different paths depending on various factors including regulatory developments, investment trends, technological breakthroughs, and market adoption. We analyze three potential scenarios:
Optimistic Scenario
Responsible AI driving innovation while minimizing societal disruption
Key Drivers: Supportive regulatory environment, significant research breakthroughs, strong market incentives, and rapid user adoption.
Probability: 25-30%
Base Case Scenario
Incremental adoption with mixed societal impacts and ongoing ethical challenges
Key Drivers: Balanced regulatory approach, steady technological progress, and selective implementation based on clear ROI.
Probability: 50-60%
Conservative Scenario
Technical and ethical barriers creating significant implementation challenges
Key Drivers: Restrictive regulations, technical limitations, implementation challenges, and risk-averse organizational cultures.
Probability: 15-20%
Scenario Comparison Matrix
| Factor | Optimistic | Base Case | Conservative |
|---|---|---|---|
| Implementation Timeline | Accelerated | Steady | Delayed |
| Market Adoption | Widespread | Selective | Limited |
| Technology Evolution | Rapid | Progressive | Incremental |
| Regulatory Environment | Supportive | Balanced | Restrictive |
| Business Impact | Transformative | Significant | Modest |
Transformational Impact
Redefinition of knowledge work, automation of creative processes. This evolution will necessitate significant changes in organizational structures, talent development, and strategic planning processes.
The convergence of multiple technological trends—including artificial intelligence, quantum computing, and ubiquitous connectivity—will create both unprecedented security challenges and innovative defensive capabilities.
Implementation Challenges
Ethical concerns, computing resource limitations, talent shortages. Organizations will need to develop comprehensive change management strategies to successfully navigate these transitions.
Regulatory uncertainty, particularly around emerging technologies like AI in security applications, will require flexible security architectures that can adapt to evolving compliance requirements.
Key Innovations to Watch
Multimodal learning, resource-efficient AI, transparent decision systems. Organizations should monitor these developments closely to maintain competitive advantages and effective security postures.
Strategic investments in research partnerships, technology pilots, and talent development will position forward-thinking organizations to leverage these innovations early in their development cycle.
Technical Glossary
Key technical terms and definitions to help understand the technologies discussed in this article.
Understanding the following technical concepts is essential for grasping the full implications of the security threats and defensive measures discussed in this article. These definitions provide context for both technical and non-technical readers.
large language model intermediate
generative AI intermediate
platform intermediate
API beginner
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