Adobe Firefly Introduces Prompt-Based Video Editing and Expands Third-Party Model Support

Adobe Firefly Revolutionizes AI Video Editing with New Features

Adobe is enhancing its AI video-generation platform, Firefly, by introducing an innovative video editor that facilitates precise prompt-based edits. This update also incorporates new third-party models for image and video generation, notably Black Forest Labs’ FLUX.2 and Topaz Astra.

Streamlined Editing with Prompt-Based Controls

Previously, Firefly limited users to full clip recreation if any aspect was unsatisfactory. The newly launched editor allows for text prompts to refine video elements, adjusting colors, camera angles, and more. Users can now easily manipulate frames, audio, and other features through an intuitive timeline view.

Introducing New Models and Features

Initially announced in October as a private beta, the video editor is now accessible to all users. With the integration of Runway’s Aleph model, creators can provide specific instructions such as “Change the sky to overcast and lower the contrast” or “Zoom in slightly on the main subject.”

Advanced Camera Manipulation and Upscaling Capabilities

Users can leverage Adobe’s own Firefly Video model to upload a starting frame and a reference video to recreate desired camera angles. Additionally, the Topaz Labs’ Astra model enables video upscaling to 1080p or 4K, while FLUX.2 will enhance image generation capabilities in the app. Moreover, a collaborative boards feature will be introduced soon.

Immediate Availability and Future Releases

FLUX.2 is now available across all platforms within Firefly, with Adobe Express users gaining access starting in January. Adobe seeks to engage more users by continually improving Firefly amid competition in image and video generation tools.

Special Offers for Firefly Subscribers

To attract users, Adobe will provide unlimited generations from all image models, including the Firefly Video Model, to subscribers of Firefly Pro, Firefly Premium, and certain credit plans until January 15.

A Year of Transformative Updates

Adobe has significantly revamped Firefly this year, launching subscriptions for varied image and video generation levels, followed by a new Firefly web app and mobile applications, alongside enhanced support for additional third-party models.

Here are five FAQs regarding Adobe Firefly’s new features:

FAQ 1: What is prompt-based video editing in Adobe Firefly?

Answer: Prompt-based video editing allows users to generate and modify video content using natural language prompts. This means you can describe what you want to see in the video, and Adobe Firefly will assist in creating or editing the footage accordingly.

FAQ 2: How does the addition of third-party models enhance Adobe Firefly’s capabilities?

Answer: The integration of third-party models expands the range of creative possibilities by allowing users access to diverse AI tools and resources. This helps in generating more customized and varied content tailored to specific needs or styles.

FAQ 3: What types of video editing tasks can I perform using Adobe Firefly’s prompt-based features?

Answer: You can perform a variety of tasks, including scene alterations, adding visual effects, color grading, and more—simply by inputting descriptive prompts. This aims to streamline the editing process and make it more intuitive.

FAQ 4: Is there a learning curve for using these new features in Adobe Firefly?

Answer: While there might be an initial adjustment period, Adobe Firefly is designed with user-friendliness in mind. Many find that using prompts simplifies tasks, making it accessible even for those with limited video editing experience.

FAQ 5: Are there any additional costs associated with using third-party models in Adobe Firefly?

Answer: The pricing structure for using third-party models may vary based on the specific models or services being utilized. It’s best to check Adobe’s official documentation or pricing page for the latest information on any additional costs.

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Nvidia Considers Increasing H200 Production to Address Rising Demand in China

Nvidia Gains Approval to Sell H200 Chips in China Amid Surge in Demand

Nvidia has successfully lobbied for approval from the Trump administration, allowing the sales of its H200 chips to China. Reports suggest the company is now poised to increase production to meet the rising orders from Chinese firms, according to Reuters sources.

H200 Chips: A Game Changer for AI Training

The H200 chips, Nvidia’s most advanced offering from the Hopper GPU generation, were previously restricted from being sold in China due to the Biden administration’s export limitations on top-tier AI chips. However, a recent decision by the Department of Commerce has cleared the way for Nvidia to sell H200 GPUs in China, resulting in a 25% sales cut to the US government.

Chinese Demand Sparks Potential Production Expansion

Faced with remarkable demand from Chinese tech companies, Nvidia is contemplating increasing its production capacity, as reported by Reuters. Nevertheless, Chinese authorities are still deliberating on permitting the import of the H200 chips, which boast significantly enhanced capabilities compared to the previous H20 models designed for the Chinese market.

Opportunities and Challenges in the Race for AI Development

For Nvidia, ramping up H200 chip production would enable the company to capitalize on the untapped demand in China, a nation eager to develop its own AI chip capabilities. Rising competition and national security anxieties in Western countries have restricted access to the latest high-performance hardware essential for AI training, prompting Chinese firms to prioritize efficiency over sheer scale.

Key Players Eager to Secure H200 Chip Orders

Major Chinese companies, including Alibaba and ByteDance, are already engaging with Nvidia to secure substantial orders for the H200 chips, which are currently in limited supply, the report indicates.

Nvidia has not yet responded to requests for comment.

Here are five FAQs regarding Nvidia’s plans to ramp up H200 production in response to surging demand in China:

FAQ 1: What is the H200?

Answer: The H200 is Nvidia’s latest high-performance GPU designed for data centers, AI applications, and advanced computing tasks. It offers significant improvements in processing power and energy efficiency, making it suitable for a wide range of applications, including machine learning and data analytics.

FAQ 2: Why is Nvidia increasing H200 production in China?

Answer: Nvidia is ramping up H200 production to meet the surging demand from the Chinese market. As companies in China increasingly invest in AI and data center technologies, Nvidia aims to ensure that its products are readily available to cater to this growing need.

FAQ 3: How does this increase in production affect prices?

Answer: While an increase in production generally aims to stabilize or lower prices by meeting demand, other factors such as global supply chain issues, manufacturing costs, and trade regulations may also affect pricing. Therefore, it’s unclear if prices will drop as a direct result of increased H200 production.

FAQ 4: When can we expect the increased production to reflect in the market?

Answer: The timeline for increased production typically depends on multiple factors, including manufacturing capacity and logistical considerations. Analysts suggest that significant changes may become evident within a few months, but specific timelines can vary.

FAQ 5: Will these changes impact Nvidia’s other products?

Answer: While the focus on increasing H200 production primarily addresses current demand, it may also affect Nvidia’s overall production strategy. Resources and attention may shift, potentially influencing the availability or development timelines of other products in the Nvidia lineup.

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AI Data Center Surge May Spell Trouble for Other Infrastructure Initiatives

Data Center Boom Threatens Infrastructure Development

Accelerating data center construction may jeopardize crucial improvements to roads, bridges, and other vital infrastructure, as highlighted by a recent Bloomberg report.

Record Debt Sales to Fund Infrastructure Projects

In 2025, state and local governments achieved record debt sales for the second consecutive year, with projections indicating an additional $600 billion in sales slated for the upcoming year. The majority of these funds are earmarked for infrastructure enhancements.

Private Sector Spending on Data Centers Surges

According to Census Bureau data, private investment in data center construction is currently exceeding an annualized rate of $41 billion, approximately equating to the spending by state and local governments on transportation initiatives.

Labor Shortages Complicate Construction Efforts

These competing construction projects are likely to contend for a limited pool of workers, particularly as the industry grapples with labor shortages caused by retirements and the effects of President Trump’s immigration policies.

Expert Insight: Data Centers Detract from Infrastructure Progress

Andrew Anagnost, CEO of Autodesk, emphasized to Bloomberg that there is “absolutely no doubt” that the surge in data center construction is diverting resources away from essential infrastructure projects. He remarked, “I guarantee you a lot of those [infrastructure] projects are not going to move as fast as people want.”

FAQ: AI Data Center Boom Impact on Infrastructure Projects

1. What is the AI data center boom?

The AI data center boom refers to the rapid growth and expansion of data centers specifically designed to support artificial intelligence applications. This trend has been driven by increasing demand for AI processing power, necessitating more robust infrastructure and energy resources.

2. Why could the growth of AI data centers negatively affect other infrastructure projects?

The massive energy and resource demands of AI data centers can divert attention and funding away from other critical infrastructure projects. As governments and companies prioritize data center construction, investments in roads, bridges, and public utilities may be delayed or scaled back.

3. What specific infrastructure projects could be impacted?

Key infrastructure projects that could face delays include renewable energy installations, public transportation enhancements, and water supply systems. Since AI data centers require significant electricity and cooling resources, existing infrastructure may struggle to accommodate these demands without significant upgrades.

4. Are there any environmental concerns associated with the AI data center boom?

Yes, the increased energy consumption from AI data centers raises concerns about carbon emissions and resource depletion. Many regions lack the necessary infrastructure to support this growth sustainably, leading to potential environmental degradation and increased energy costs for local communities.

5. What can be done to mitigate the negative effects on infrastructure from the AI data center expansion?

To alleviate the issues, comprehensive planning is essential. Policymakers and industry leaders should collaborate on sustainable energy solutions, prioritize balanced investment across infrastructure sectors, and assess the long-term impacts of AI data centers on community resources to ensure equitable development.

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What’s Happening with LinkedIn’s Algorithm?

<div>
    <h2>LinkedIn Gender Experiment Raises Questions About Algorithm Bias</h2>

    <p id="speakable-summary" class="wp-block-paragraph">In November, a product strategist, whom we'll refer to as Michelle (a pseudonym), logged into her LinkedIn profile and switched her gender to male, changing her name to Michael. This was part of an experiment called #WearthePants, designed to explore potential biases in LinkedIn's algorithm against women.</p>

    <h3>The #WearthePants Experiment: Testing Algorithmic Bias</h3>

    <p class="wp-block-paragraph">Michelle was participating in a growing trend where women sought to verify claims of algorithmic bias on LinkedIn. The test came in response to observations by frequent users who noted decreased engagement and visibility on their posts, coinciding with recent algorithm updates.</p>

    <h3>Engagement Imbalances: A Closer Look</h3>

    <p class="wp-block-paragraph">With over 10,000 followers, Michelle ghostwrites for her husband, whose profile has about 2,000 followers. Surprisingly, both received similar engagement despite the follower disparity. “The only significant variable was gender,” she pointed out.</p>

    <h3>User Reports of Gender-Based Visibility Changes</h3>

    <p class="wp-block-paragraph">Users like Marilynn Joyner also noted stark differences after changing their gender on LinkedIn. After switching to male, she reported a 238% increase in post impressions within just one day. This trend was echoed by many, leading to discussions surrounding gender bias within the platform.</p>

    <h3>The Response from LinkedIn: No Bias, No Problem?</h3>

    <p class="wp-block-paragraph">In response to these claims, LinkedIn stated that its algorithms do not rely on demographic information to determine visibility in users’ feeds. Yet, experts have noted that implicit biases may still persist within the system.</p>

    <h3>Understanding the Algorithm: Complexity and Bias</h3>

    <p class="wp-block-paragraph">According to data ethics consultant Brandeis Marshall, LinkedIn's algorithms are complex and may inadvertently favor certain communication styles. This complexity makes it difficult to pinpoint specific causes for visibility variations.</p>

    <h3>Roots of the #WearthePants Movement</h3>

    <p class="wp-block-paragraph">The #WearthePants initiative originated from entrepreneurs Cindy Gallop and Jane Evans, who questioned if gender was influencing engagement levels. By having men post similar content, they highlighted stark discrepancies in reach.</p>

    <h3>Algorithmic Transparency: A Call to Action</h3>

    <p class="wp-block-paragraph">While some participants demand accountability from LinkedIn regarding potential bias, the company's secrecy about algorithm operations complicates the issue. Marshall emphasizes the need for platforms like LinkedIn to address biases that might stem from the way their AI systems are trained.</p>

    <h3>User Experiences: Mixed Reviews on Engagement</h3>

    <p class="wp-block-paragraph">Many users across genders express frustration with the new algorithm. While some see increased impressions, others struggle to achieve engagement levels similar to those prior to the changes.</p>

    <h3>The Search for Clarity and Fairness</h3>

    <p class="wp-block-paragraph">The algorithm's opaque nature means that users are left confused and seeking clarity. “I want transparency,” Michelle stated, encapsulating the broader demand for accountability in social media platforms.</p>
</div>

This rewrite preserves the core content while enhancing SEO with structured headings and concise summaries that engage the reader.

Here are five FAQs regarding LinkedIn’s algorithm:

FAQ 1: What does LinkedIn’s algorithm prioritize in user feeds?

Answer: LinkedIn’s algorithm prioritizes content that encourages engagement, such as likes, comments, and shares. It looks for posts that are relevant to your interests, industry, and connections, promoting high-quality, meaningful interactions over irrelevant content.

FAQ 2: How can I improve the visibility of my posts on LinkedIn?

Answer: To enhance the visibility of your posts, focus on creating engaging, original content that sparks conversation. Use relevant hashtags, tag connections, and post during peak hours when your audience is most active. Consistent interaction with your network also boosts your overall visibility.

FAQ 3: Are videos prioritized over text posts?

Answer: Yes, the algorithm tends to favor video content, as it often generates higher engagement rates. Incorporating video into your LinkedIn strategy can help attract more views and interactions compared to traditional text posts or images.

FAQ 4: Does commenting on others’ posts affect my own reach?

Answer: Absolutely! Engaging with others’ posts can expand your network and enhance your own visibility. When you comment on posts, your name is visible to the original poster’s connections, potentially increasing your reach and encouraging reciprocal engagement.

FAQ 5: How does LinkedIn determine what’s “high-quality” content?

Answer: LinkedIn assesses content quality based on user engagement metrics, relevance, and whether it fosters conversation. Posts that result in meaningful discussions, high interaction rates, and positive feedback from users are considered high-quality and are more likely to be promoted in feeds.

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Google Unveils Its Most Advanced AI Research Agent on the Same Day OpenAI Releases GPT-5.2

Google Unveils Enhanced Gemini Deep Research Agent Powered by Gemini 3 Pro

On Thursday, Google unveiled a revamped version of its research agent, Gemini Deep Research, now enhanced with the cutting-edge Gemini 3 Pro foundation model.

Empowering Developers with New Research Capabilities

This updated agent goes beyond generating research reports to allow developers to integrate Google’s state-of-the-art research functionalities into their own applications through the new Interactions API. This innovation marks a significant advancement in the evolving landscape of agentic AI.

Versatile Solutions for Diverse Applications

The latest Gemini Deep Research tool is adept at synthesizing vast amounts of data, capable of managing substantial context within prompts. Google highlights its use for a variety of purposes, including due diligence and drug toxicity investigations.

Integrating AI Into Everyday Services

Google plans to weave this new deep research agent into key platforms, including Google Search, Google Finance, Gemini App, and its widely utilized NotebookLM. This strategy anticipates a future where AI agents will handle information queries, reducing the need for users to search online themselves.

Minimizing AI Hallucinations for Enhanced Accuracy

The Deep Research tool benefits significantly from Gemini 3 Pro’s status as the “most factual” model, specifically designed to reduce hallucinations, a pressing issue during complex, long-term reasoning tasks.

New Benchmark: DeepSearchQA

To validate its capabilities, Google introduced the DeepSearchQA benchmark, tailored for evaluating agents on intricate, multi-step information-seeking tasks, which has been made open source for broader community use.

Performance Comparisons with Other Leading AI

Additionally, Google tested Deep Research on the intriguingly named Humanity’s Last Exam and BrowserComp benchmarks. While Google’s new agent excelled in its own tests and Humanity’s, OpenAI’s ChatGPT 5 Pro emerged as a robust competitor, slightly outperforming Google on BrowserComp.

Rivalry Heating Up: OpenAI Launches GPT 5.2

The benchmark announcements from Google coincided with OpenAI’s release of the much-anticipated GPT 5.2, codenamed Garlic. OpenAI posits that its latest model outperforms competitors in crucial benchmark tests, including its own.

Strategic Timing for AI Announcements

The timing of Google’s announcement seems strategic, as it aims to capture attention amidst the buzz surrounding OpenAI’s Garlic, highlighting its commitment to innovation in AI technologies.

Sure! Here are five FAQs regarding Google’s latest AI research agent launch, coinciding with OpenAI’s release of GPT-5.2.

FAQ 1: What is Google’s new AI research agent?

Answer: Google’s new AI research agent is its deepest and most sophisticated artificial intelligence model to date. It leverages advanced machine learning techniques to enhance natural language understanding, improve conversational capabilities, and support a wide range of applications, from research assistance to creative content generation.

FAQ 2: How does this release compare to OpenAI’s GPT-5.2?

Answer: While both Google’s new AI agent and OpenAI’s GPT-5.2 push the boundaries of natural language processing, they may differ in specific capabilities, underlying architecture, and intended use cases. Google’s model is designed to enhance interactive and contextual understanding, while GPT-5.2 focuses on refining conversational flow and accuracy.

FAQ 3: What are the potential applications of Google’s AI research agent?

Answer: Google’s AI research agent can be applied in various fields, including customer service, content creation, coding assistance, and educational tools. Its advanced capabilities are aimed at improving user interactions, delivering personalized experiences, and aiding researchers in data analysis.

FAQ 4: Are there any ethical concerns associated with these AI advancements?

Answer: Yes, with the advancement of AI technology comes ethical considerations, including bias in algorithms, privacy concerns, and potential job displacement. Both Google and OpenAI emphasize the importance of developing these technologies responsibly and are actively working on guidelines to address these issues.

FAQ 5: How can users access Google’s new AI research agent?

Answer: Google is expected to gradually roll out its new AI research agent through its existing products, like Google Search and Workspace tools. Users may also find dedicated AI applications or APIs available for developers looking to integrate this technology into their platforms, though specific access details haven’t been fully implemented yet.

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Interest in Spoor’s AI Software for Bird Monitoring is Skyrocketing

Spoor: Pioneering Computer Vision Technology to Protect Bird Populations from Wind Turbines

Spoor, founded in 2021, aims to harness computer vision to mitigate the impact of wind turbines on local bird species. The startup has validated its technology and is witnessing increasing demand from wind farms and other sectors.

Innovative Technology Tracking Bird Migration Patterns

Based in Oslo, Norway, Spoor has developed advanced software that utilizes computer vision to monitor and identify bird populations and their migration routes. This technology can detect birds within a 2.5-kilometer range (approximately 1.5 miles) and is compatible with any standard high-resolution camera.

Enhancing Wind Farm Operations through Smart Data

Wind farm operators can leverage this crucial information to strategically determine wind farm placements and better understand migration patterns. They can even adjust turbine operations—slowing or stopping them—during peak migration times to protect bird populations.

A Passion for Conservation: Insights from Spoor’s Co-Founder

Ask Helseth, co-founder and CEO of Spoor, shared his motivation with TechCrunch last year, citing the lack of effective tracking tools in the wind farm industry despite stringent regulations governing their operations and their impact on local avifauna.

“Regulators are raising expectations, yet the industry lacks adequate solutions,” Helseth noted. “Many field assessments still rely on binoculars and trained dogs to tally bird collisions with turbines.”

Inflated Capabilities: From 1 km to 2.5 km

Since its seed funding round in 2024, Spoor has expanded its tracking capabilities from a 1-kilometer range to a powerful 2.5 kilometers. This enhancement has led to a remarkable 96% accuracy in bird identification, thanks to an influx of data feeding into their AI algorithms.

Collaborations and Future Expansions

Spoor now operates on three continents and collaborates with over 20 leading energy companies worldwide. The startup is also generating interest from diverse sectors, including airports and aquaculture, and has partnered with mining giant Rio Tinto to monitor bat populations.

Exploring New Opportunities with Caution

While there is growing curiosity about using Spoor’s technology to track other small objects, such as drones, Helseth humorously noted, “Drones, in our view, are like plastic birds. They possess a different movement pattern and structure, so we are currently not focusing on collecting that data.”

Funding and Future Aspirations

Spoor successfully secured an €8 million ($9.3 million) Series A funding round, led by SET Ventures, with contributions from Ørstead Ventures and Superorganism, along with other strategic investors.

Helseth anticipates a growing demand for this kind of technology as regulatory scrutiny intensifies. Recently, French authorities shut down a wind farm due to its adverse effects on local bird species, imposing hefty fines in the process.

“Our mission is to ensure harmony between industry and nature,” Helseth concluded. “While we’ve made strides, we remain a small startup with much to demonstrate. Our goal is to solidify our status in the wind sector and to evolve as a global leader in addressing these pressing challenges, while also showing the wider value of our technology.”

Here are five FAQs regarding Spoor’s bird monitoring AI software:

FAQ 1: What is Spoor’s bird monitoring AI software?

Answer: Spoor’s bird monitoring AI software utilizes advanced artificial intelligence algorithms to analyze bird populations, track species movement, and gather data on their habitats. This software assists researchers and conservationists in understanding avian behaviors and making informed decisions for species protection.

FAQ 2: How does Spoor’s AI software improve bird monitoring?

Answer: The software enhances bird monitoring by automating data collection and analysis, allowing for more efficient tracking of various species. It can process vast amounts of audio and visual data, identify species, and detect behavioral patterns, significantly reducing the time and manpower needed for traditional monitoring methods.

FAQ 3: Who can benefit from using Spoor’s bird monitoring AI software?

Answer: The software is beneficial for researchers, conservation organizations, wildlife enthusiasts, and educators. It serves as a valuable tool for anyone interested in avian studies, habitat conservation, and biodiversity assessment.

FAQ 4: Is Spoor’s bird monitoring AI software user-friendly?

Answer: Yes, Spoor’s software is designed with user-friendliness in mind. It features an intuitive interface that requires minimal technical expertise. Comprehensive tutorials and support resources are also available to assist users in navigating the software effectively.

FAQ 5: How can I get started with Spoor’s bird monitoring AI software?

Answer: To get started, visit Spoor’s official website to request a demo or download the software. You may also explore subscription options suitable for individual or organizational use. Getting in touch with their support team can provide further guidance on implementation and features.

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Figma Unveils AI-Driven Object Removal and Image Extension Features

Figma Unveils Cutting-Edge AI-Powered Image Editing Features

Today, Figma announced exciting new AI-driven capabilities, including advanced object removal, isolation, and image expansion.

Streamlined Editing: No More Exporting Hassles

Figma’s latest features aim to simplify the editing process by eliminating the need to export images to third-party tools. While AI generation models like Nano Banana excel at creating images, users often require precise editing tools that don’t rely on text prompts.

Enhanced Lasso Tool: Effortless Object Manipulation

The revamped lasso tool now allows users to effortlessly select, remove, or isolate objects. Even when moved, the object retains essential image characteristics, such as background and color. Users can fine-tune aspects like lighting, shadow, color, and focus directly within Figma.

Image Expansion: Flexibility for Creative Formats

Figma introduces a valuable image expansion feature, particularly useful for adapting designs to different formats. This tool allows users to easily fill in backgrounds or other details, saving time on cropping and element adjustments when creating assets like web or mobile banners.

Image Credits: Figma

Centralized Toolbar: All Your Editing Tools in One Place

In addition to these features, Figma is consolidating its image editing tools into a single toolbar for easy access. Users can now select objects, change background colors, and add annotations seamlessly. Recognizing that background removal is one of the platform’s most popular actions, Figma has ensured it features prominently in the new toolbar.

Figma Joins the Ranks of Competitors with Object Removal

While industry giants like Adobe and Canva have offered object removal features for some time, Figma is now stepping up to meet user demands.

Availability and Future Plans

These innovative image editing features are currently accessible on Figma Design and Draw, with plans for broader availability across Figma tools next year.

Coinciding Launch with Adobe’s New ChatGPT Features

In a related development, Adobe also rolled out similar features for ChatGPT users today. Figma was a launch partner for the app in October, although it’s still unclear if the new functions will be integrated for Figma users within OpenAI’s tool.

Here are five FAQs with answers regarding Figma’s new AI-powered object removal and image extension features:

FAQ 1: What is the AI-powered object removal feature in Figma?

Answer: The AI-powered object removal feature in Figma allows users to easily eliminate unwanted elements from images. Utilizing advanced algorithms, it intelligently fills in the background after an object is removed, ensuring a seamless look.

FAQ 2: How can I use the image extension feature in Figma?

Answer: The image extension feature enables users to expand images beyond their original dimensions. You can simply select an image and use the extension tool to add more visual content while maintaining the overall style and coherence of the design.

FAQ 3: Is the AI object removal feature available in all Figma plans?

Answer: Yes, the AI object removal feature is available to all Figma users, regardless of their subscription plan. However, some enhanced functionalities may be limited to specific tiers or require additional plugins.

FAQ 4: How does the AI technology work for object removal?

Answer: The AI technology leverages machine learning models trained on vast datasets to identify and comprehend the context of images. When an object is removed, the algorithm predicts and generates the background image content, ensuring that the edit looks natural.

FAQ 5: Can I use the object removal and image extension features on mobile devices?

Answer: Currently, the object removal and image extension features are optimized for the Figma web and desktop applications. Mobile access may provide limited functionality, with full features available on larger screens.

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Empromptu Secures $2M in Pre-Seed Funding to Enable Enterprises in Developing AI Applications

Sheena Leven Unveils Lessons Learned from Launching CodeSee and New AI Venture Empromptu

Sheena Leven, the visionary entrepreneur behind CodeSee, shares key insights gained from her journey in tech startups. From distinguishing genuine business needs to embracing foundational principles, her experience sets the stage for her next innovative project.

The Fundamentals Never Fade Away

“Security, compliance, reliability, quality—these essentials remain critical for enterprise applications,” Leven emphasizes.

Introducing Empromptu: Empowering Non-Technical Business Owners

Following the acquisition of CodeSee in 2024, Leven’s vision shifted towards creating a platform that enables business owners, regardless of their technical expertise, to develop AI applications. Partnering with AI researcher Sean Robinson, they launched Empromptu last October, providing an accessible AI service for businesses.

User-Friendly AI Development at Your Fingertips

Empromptu enables users to simply describe their needs to the AI chatbot—whether they want a new HTML or JavaScript app—and the platform will create it. Additionally, it offers LLM (Large Language Model) tools for further refining results and allows companies to seamlessly integrate AI features into their existing code bases.

Not Just Vibe Coding: Transforming Ideas into Real Software

Leven distinguishes Empromptu from vibe-coding platforms, though she anticipates competition from companies like Replit and Lovable. “Vibe coding is ideal for quick experiments, but Empromptu is designed to convert those experiments into fully-fledged software,” she states.

Funding Fuel for Growth and Innovation

In a recent announcement, Empromptu revealed a successful $2 million pre-seed funding round led by Precursor Ventures, supported by Zeal Capital, Alumni Ventures, Founders Edge, and South Loop.

Investing in the Future: Targeting Complex Industries

The newly acquired funds will be allocated towards expanding the team and developing proprietary technology. Empromptu aims to cater to businesses in regulated sectors and complex fields, such as software solutions for the hospitality industry.

Making AI Accessible for All Founders

Ultimately, Leven envisions a world where founders can transform their businesses without needing extensive technical knowledge. “It’s just like any other skill,” she remarks. “The beauty is that AI can guide you as you learn.”

Here are five FAQs based on the news that Empromptu has raised $2M in pre-seed funding to assist enterprises in building AI applications:

FAQ 1: What is Empromptu?

Answer: Empromptu is a technology startup focused on helping enterprises create artificial intelligence applications. The company provides tools and platforms that simplify the development process, enabling businesses to leverage AI for various operational needs.

FAQ 2: How much funding did Empromptu raise, and in what stage?

Answer: Empromptu successfully raised $2 million in a pre-seed funding round. This initial investment will support the development of its AI application-building platform and accelerate its market entry.

FAQ 3: What will the funding be used for?

Answer: The $2 million in pre-seed funding will be utilized to enhance Empromptu’s technology, expand its development team, and accelerate product marketing efforts to help enterprises effectively build and deploy AI applications.

FAQ 4: Who are the investors involved in this funding round?

Answer: While specific investors have not all been publicly disclosed, the pre-seed funding round included participation from notable angel investors and venture capitalists who specialize in technology and AI sectors.

FAQ 5: How can enterprises benefit from using Empromptu’s platform?

Answer: Enterprises using Empromptu’s platform can streamline their AI application development process, reduce time-to-market, and leverage advanced AI capabilities without needing deep technical expertise. This empowers organizations to innovate and enhance operational efficiency through custom AI solutions.

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Hinge’s AI Feature Transforms Dating by Elevating Conversations Beyond Small Talk

Hinge Launches AI-Powered “Convo Starters” to Spark Meaningful Conversations

Many daters on Hinge are expressing their frustration with matches who simply like their profiles without initiating conversations. This often causes an uncomfortable silence, placing the onus on one person to break the ice. Unfortunately, many resort to clichéd lines or mundane small talk, such as “How are you?”

Revolutionizing Connections with AI

To tackle this issue, Hinge has introduced “Convo Starters,” an innovative feature powered by AI that offers personalized suggestions for opening dialogues.

Empowering Daters with Tailored Suggestions

This feature aims to inspire users and bolster their confidence when sending initial messages. When users like a profile, they’ll now see three customized tips beneath each photo and prompt. The AI evaluates a user’s profile and generates recommendations based on individual images or prompts. For instance, if a potential match is shown playing chess, Hinge might suggest starting the conversation with a query about board games.

Hinge Convo Starters Screenshot
Image Credits: Hinge

Backed by User Insights

The launch of Convo Starters is a response to user feedback. Hinge’s research revealed that 72% of its users are more likely to engage with someone when a like is paired with a message. The data shows that users who comment alongside their likes are twice as likely to secure dates.

Continuing the AI Evolution

This feature builds on the introduction of Hinge’s AI-driven Prompt Feedback, which assesses user prompts and provides tailored advice to enhance them, encouraging users to share more engaging details about their lives.

Addressing User Concerns

Despite the benefits of AI features, many users—particularly Gen Z—express discomfort with AI in online dating. A Bloomberg Intelligence survey indicates that Gen Z is more hesitant than older generations about using AI for tasks such as crafting profile prompts and responding to messages.

Investing in the Future of AI Dating

Hinge’s parent company, Match Group, is committing approximately $20 million to $30 million towards advancing its AI initiatives.

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Sure! Here are five FAQs about Hinge’s new AI feature designed to enhance dating conversations:

1. What is Hinge’s new AI feature?

Answer: Hinge’s new AI feature assists users in crafting engaging responses and prompts, helping them move beyond typical small talk, thereby fostering deeper connections. It generates tailored suggestions that enhance conversation flow based on user interests and preferences.

2. How does the AI suggest conversation topics?

Answer: The AI analyzes user profiles, personal interests, and past conversation patterns to suggest relatable topics or engaging questions. This ensures that the prompts feel personalized and relevant, making it easier for users to connect on a more meaningful level.

3. Can I customize the AI suggestions?

Answer: Yes! Users have the option to refine AI-generated prompts based on their preferences. You can specify the type of conversations you enjoy or indicate topics you’d like to avoid, allowing for a more tailored dating experience.

4. Is using the AI feature free?

Answer: The AI feature is integrated into Hinge’s app and is available to both free and premium users. While some advanced functionalities may require a subscription, the core features designed to assist in engaging conversation are accessible to all users.

5. Will the AI take over my conversations?

Answer: No, the AI is designed to assist, not replace. It offers suggestions and prompts to enhance your interactions, but users maintain full control over their conversations. You can choose to use the AI’s suggestions or continue chatting in your own style.

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Pat Gelsinger Seeks to Preserve Moore’s Law with Support from the Federal Government

Pat Gelsinger’s New Chapter: Leading xLight in the Semiconductor Arena

After a tumultuous exit from Intel, Pat Gelsinger continues to rise at dawn, navigating the complex semiconductor landscape from a fresh vantage point. As a general partner at Playground Global, Gelsinger is invested in 10 startups, with xLight—a promising semiconductor firm—drawing significant focus. Recently, xLight announced a preliminary agreement for up to $150 million from the U.S. Commerce Department, making the government a key stakeholder.

A Major Win After Intel

Gelsinger’s 35-year journey at Intel came to an unexpected end when the board dismissed him due to doubts about his revival strategies. Nevertheless, the xLight partnership highlights a new trend that raises eyebrows in Silicon Valley: the Trump administration’s willingness to take equity in essential tech companies.

Silicon Valley’s Unease

California Governor Gavin Newsom expressed the industry’s discomfort at a recent event, questioning, “What happened to free enterprise?” This sentiment reverberates through a tech sector historically rooted in free-market ideals.

Driving Innovation in Lithography

During a TechCrunch StrictlyVC event, Gelsinger, who holds the role of executive chairman at xLight, wasn’t fazed by these concerns. His focus is on tackling a crucial bottleneck in semiconductor production: lithography. xLight aims to develop large-scale “free electron lasers” powered by particle accelerators, potentially transforming chip manufacturing processes.

Reviving Moore’s Law

“I’m dedicated to revitalizing Moore’s law in semiconductor technology,” Gelsinger stated, referencing the foundational belief that computing power doubles biennially. “We believe this innovation will reinvigorate Moore’s law.”

Securing Future Funding

The xLight deal marks the inaugural Chips and Science Act award during Trump’s second term and is part of funds designated for promising early-stage firms. While the funding is currently in the letter of intent phase, Gelsinger remained transparent about the complexities involved: “We’ve agreed in principle, but we still have work to do.”

Ambitious Technological Developments

xLight’s vision encompasses creating colossal machines—approximately 100 meters by 50 meters—that will generate extreme ultraviolet light at remarkably precise wavelengths of 2 nanometers. This surpasses the capabilities of ASML, the industry leader dominating the EUV lithography market.

Transforming the Light Source Paradigm

“Half of the semiconductor industry’s investment goes into lithography,” Gelsinger explained. “Innovating on light wavelength and power is crucial for advancing semiconductor technology.” Leading xLight, Nicholas Kelez brings a unique perspective from his experience in quantum computing and large-scale X-ray science initiatives.

Embracing Viability in New Technologies

Kelez highlighted why xLight’s approach is feasible now, contrasting it with ASML’s previous abandonment of a similar strategy. The industry is now primed for this innovation, bolstered by advancements and the ubiquity of EUV lithography in semiconductor manufacturing.

Looking Ahead to 2028

With ambitions of producing silicon wafers by 2028 and launching a commercial system by 2029, xLight is poised for significant growth.

Collaborative Strategies

xLight is not directly competing with ASML but rather collaborating to integrate their systems. Gelsinger mentioned that while there are no contracts from major chipmakers yet, discussions are ongoing with potential partners.

Navigating Complex Competitive Dynamics

As competition intensifies, other startups like Substrate are emerging with similar technologies. However, Gelsinger views them as potential collaborators rather than rivals.

Political Underpinnings of xLight’s Funding

Gelsinger’s engagement with the Trump administration adds complexity to the narrative. Earlier discussions with Secretary of Commerce Howard Lutnick paved the way for this significant funding. While recent developments fueled criticism from some quarters, Gelsinger remains steadfast in framing government engagement as vital for national competitiveness.

Minimal Strings Attached

According to Kelez, the government investment comes with few conditions, allowing xLight the freedom to innovate without heavy oversight. With plans to raise additional funds soon, Gelsinger is optimistic about xLight’s trajectory.

Paving a New Path in Semiconductor Tech

Ultimately, xLight represents more than just another venture for Gelsinger; it’s an opportunity to reinforce his influence in the semiconductor landscape he helped shape, even as he navigates the shifting tides of Silicon Valley ethics.

A Commitment to Corporate Leadership

Gelsinger emphasizes the need for corporate leaders to remain above political fray, claiming, “CEOs and companies should neither be Republican nor Democrat.” He believes the primary goal is achieving business objectives while navigating beneficial policies, regardless of their political origin.

Reflecting on New Opportunities

In response to queries about managing multiple startups post-Intel, Gelsinger expressed contentment, asserting that influencing a broad spectrum of technologies excites him. “I’m just grateful the Playground team welcomed me,” he remarked, before humorously adding, “And I gave my wife back her weekends.” While this may seem a light comment, those familiar with Gelsinger’s work ethic might ponder how long this arrangement will hold.

Sure! Here are five FAQs related to Pat Gelsinger’s efforts to support Moore’s Law with assistance from the federal government:

FAQ 1: Who is Pat Gelsinger?

Answer: Pat Gelsinger is the CEO of Intel Corporation and a prominent figure in the tech industry. He has been an advocate for advancing semiconductor technology and maintaining the pace of innovation encapsulated by Moore’s Law, which predicts the doubling of transistors on a microchip approximately every two years.

FAQ 2: What is Moore’s Law?

Answer: Moore’s Law is an observation made by Gordon Moore, co-founder of Intel, which states that the number of transistors on a microchip doubles approximately every two years, leading to an increase in computing power and efficiency. It has been a driving principle behind the rapid advancement of technology.

FAQ 3: How does Pat Gelsinger plan to save Moore’s Law?

Answer: Pat Gelsinger aims to save Moore’s Law by advocating for increased investments in semiconductor research and development. He seeks collaboration with the federal government to support legislation and funding that would enhance the U.S. semiconductor manufacturing capabilities, ensuring innovation continues at the pace that Moore’s Law describes.

FAQ 4: What role does the federal government play in this initiative?

Answer: The federal government can provide financial support and incentives, helping to foster research and development in semiconductor technology. This includes potential funding for manufacturing facilities, tax incentives for companies investing in advanced technologies, and support for educational programs to develop a skilled workforce in the technology sector.

FAQ 5: Why is it important to maintain Moore’s Law?

Answer: Maintaining Moore’s Law is crucial because it drives technological advancements that are foundational to various industries, including computing, telecommunications, and consumer electronics. Continued progress under Moore’s Law leads to faster, cheaper, and more efficient computing solutions, ultimately benefiting society through better technologies in healthcare, transportation, and many other fields.

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