Google's new 'Ask For Me' AI tool calls businesses to get your questions answered - Related to invites, here's, advancing, works, new
Advancing discovery of better drugs and medicine
With the help of AlphaFold, researchers are designing more effective drugs like never before.
Karen Akinsanya is President of R&D, Therapeutics, at Schrödinger in New York City. She shares her AlphaFold story.
What has always captivated me is the idea that you can go from the bench to the bedside.
I have worked in academia and in drug discovery and development. This means I’ve not only studied proteins and genes and understand how to make a therapeutic molecule against a disease-causing target, but I’ve also been at the bedside of a patient as they receive that new medicine.
But the real question is, how can we improve the way we do that? People are still dying of cancer and heart disease every single day while they wait for us to find solutions.
I always say that mother nature is thrifty. When you come across a target for a new drug, you often find other potential targets that are like brothers and sisters and cousins. Each target is a protein on the surface of a cell that the drug binds to, called a receptor. The challenge for people working in drug discovery is finding a drug or molecule that binds one member of that family - the target - and inhibits that family member, but doesn’t inhibit the rest of the family. In part, this is where AlphaFold has worked so brilliantly for us.
In some cases AlphaFold - in combination with our own physics-based software that simulates how atoms interact - is enabling us to begin to simulate not just what single family members are doing, but how different family groups are behaving.
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Google's new 'Ask For Me' AI tool calls businesses to get your questions answered
Hate calling a business to ask about pricing? A new Google feature can handle that for you.
A feature called "Ask for Me" has popped up under the AI experiments category in Google Labs. Instead of calling a enterprise yourself, you can let Google's AI do it for you, handling tasks like finding the best price and checking product availability.
When you use Ask for Me, a realistic-sounding AI will contact businesses, compile options, and get back to you within 30 minutes. It works much like the Duplex feature from 2019, which would call a restaurant for you to place a reservation.
Also: Google's new AI tool is changing the way teams work and organize research.
The feature is in an experimental phase, Google warns, and isn't available for all service types. Google didn't specify exactly which services it is available for, but images only show requests for auto maintenance and nail salon pricing. The description says it's for "local services like 'oil change' or 'nail salons nearby,'" so it's possible that's it for now.
Ask for Me works in either the Chrome web browser for desktop or mobile. It's not fully open to the public yet, so you'll need to head to the Ask for me page on Google Labs to join the waitlist.
In example images, Google exhibits how the feature works.
When you search for an eligible business, an "Ask for Me" button will appear. Tap it, and you'll see options to choose from. The auto service business reveals choices like tire rotation, filter replacement, tire balancing, oil change, and scheduled maintenance. The nail salon reveals choices like nail art, gel manicure, acrylic manicure, dip powder, or polish change.
Also: Gemini's Deep Research browses the web for you - try the Android app now for free.
Given how common robocalls are these days, you have to wonder if businesses will take the time to talk to a robot, especially when the feature is so new. Call screening is my favorite thing about owning a Google Pixel, and I still find that a lot of people are hesitant to talk to a computer.
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Try Apple's new Invites app for planning your next event - here's how it works
When you're inviting friends, family, or co-workers to an event, the most convenient option is to share the event details via text. However, this typically requires either individually texting everyone the details or creating a group chat with a bunch of people who don't know each other -- a recipe for disaster.
Also: The best note-taking apps for iPad of 2025: Expert tested.
To enhance how those interactions take place, online invitation platforms like Partiful have become popular, enabling consumers to create and share invites all within one app. Today, Apple launched its version, an app called Invites that is integrated into the Apple ecosystem for a more seamless experience.
On Tuesday, Apple launched Invites, a standalone app for creating custom invitations, sharing them with a group of people, and RSVPing. Although similar apps already exist, Invites' key advantage is its integration with other Apple apps.
For example, Invites clients can collaborate on Apple Music Playlists, add photos to Shared Albums, leverage Maps within the invite to navigate to the event, and even get the forecast for the day through the Weather app.
"Apple Invites brings together capabilities our individuals already know and love across iPhone, iCloud, and Apple Music, making it easy to plan special events," mentioned Brent Chiu-Watson, Apple's senior director of Worldwide Product Marketing for Apps and iCloud.
Creating an invite is as simple as choosing a background, which can be an image from your photo library, or from the app's gallery of backgrounds. Apple Intelligence can assist in making the invites, with the built-in Image Playground generator creating images from simple prompts to match your vision for the invite. Apple Intelligence's Writing Tools can help generate the copy.
Also: App fatigue is real: customers are downloading fewer apps than ever.
Sharing the invite with others is simple: consumers can share the invite via a link and manage the preview of what others see. Guests can RSVP using the iPhone app or the web even if they don't have an Apple account or subscription.
The Invites app is free to download from the App Store for all iPhone models running iOS 18 or later. The experience is also accessible from the web at the standalone site.
SOPA Images / Contributor / Getty Images.
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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 Your Advancing Discovery 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.
platform intermediate
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