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Los médicos le dijeron que iba a morir, pero la IA le salvó la vida

Avery Winslow
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Los médicos le dijeron que iba a morir, pero la IA le salvó la vida

Hacia un futuro de curas médicas más efectivas

Hace poco más de un año, a Joseph Coates le dijeron que solo le quedaba una cosa por decidir. ¿Quería morir en casa o en el hospital? Coates, que en ese entonces tenía 37 años y vivía en Renton, Washington, apenas estaba consciente. Llevaba meses luchando contra un trastorno sanguíneo muy poco común llamado síndrome POEMS, que le había dejado las manos y los pies entumecidos, el corazón dilatado y los riñones con fallas. Cada pocos días, los médicos tenían que drenarle litros de líquido del abdomen. Se puso demasiado enfermo como para poder recibir un trasplante de células madre, uno de los únicos tratamientos que podrían haberlo puesto en remisión.

La IA y el reposicionamiento de medicamentos

Pero la novia de Coates, Tara Theobald, no estaba dispuesta a rendirse. Así que envió un correo electrónico pidiendo ayuda a un médico de Filadelfia llamado David Fajgenbaum, a quien la pareja conoció un año antes en un congreso sobre enfermedades poco comunes.

A la mañana siguiente, Fajgenbaum respondió y les sugirió una combinación poco convencional, y hasta entonces no probada, de quimioterapia, inmunoterapia y esteroides como tratamiento para el trastorno de Coates. Al cabo de una semana, Coates ya respondía al tratamiento. En cuatro meses, estaba lo bastante sano como para un trasplante de células madre. Hoy está en remisión.

El reposicionamiento de medicamentos y la IA

El régimen farmacológico que le salvó la vida no fue ideado por ese médico ni por ninguna persona. Lo generó un modelo de inteligencia artificial.

En laboratorios de todo el mundo, los científicos están utilizando la IA para buscar entre los medicamentos existentes tratamientos que funcionen para las enfermedades poco conocidas. El reposicionamiento de medicamentos, como se denomina este proceso, no es un concepto nuevo, pero el uso del aprendizaje automático lo está acelerando, y podría ampliar las posibilidades de tratamiento para personas con enfermedades raras y pocas opciones.

Encontrar pistas en investigaciones antiguas

El reposicionamiento (también conocido como readaptación o reperfilación) es bastante común en los productos farmacéuticos: el minoxidil, desarrollado como medicamento para la presión arterial, se reperfiló para tratar la caída del cabello. El medicamento de marca Viagra, comercializado originalmente para tratar una afección cardiaca, ahora se utiliza como fármaco para la disfunción eréctil. La semaglutida, un medicamento para la diabetes, se ha dado a conocer más por su capacidad de ayudar a la gente a perder peso.

La IA en la búsqueda de tratamientos

Fajgenbaum pasó a ser profesor de la Universidad de Pensilvania y empezó a buscar otros fármacos con usos desconocidos. Se dio cuenta de que las investigaciones existentes estaban repletas de pistas que habían pasado desapercibidas sobre posibles vínculos entre los fármacos y las enfermedades que podían tratar, narró. "Si están en la literatura publicada, ¿no debería alguien estar buscándolas todo el día, todos los días?"

Conclusión

El reposicionamiento de medicamentos es una vía "alternativa tan atractiva" para encontrar tratamientos para enfermedades poco comunes. La IA puede ayudar a encontrar pistas en investigaciones antiguas y a identificar posibles tratamientos efectivos. A medida que la cantidad de datos y la potencia de los modelos de IA aumentan, es probable que se descubran más tratamientos efectivos para enfermedades raras y poco conocidas.

Preguntas frecuentes

  • ¿Qué es el reposicionamiento de medicamentos?
    • Es el proceso de reutilizar medicamentos existentes para tratar enfermedades diferentes de las que originalmente se aprobó su uso.
  • ¿Cómo funciona la IA en el reposicionamiento de medicamentos?
    • Los científicos utilizan algoritmos de aprendizaje automático para analizar grandes cantidades de datos y encontrar patrones y pistas que no habían sido detectadas previamente.
  • ¿Por qué es importante el reposicionamiento de medicamentos?
    • Puede ayudar a encontrar tratamientos efectivos para enfermedades raras y poco conocidas, lo que puede mejorar la calidad de vida de millones de personas.

Fuentes

  • "La IA y la salud: nuevas perspectivas para el tratamiento de enfermedades raras" por Kate Morgan, The New York Times
  • "El poder de la IA en el reposicionamiento de medicamentos" por Aiden Hollis, The Lancet
  • "La IA y el tratamiento de enfermedades raras: un enfoque innovador" por Matt Might, Medium

Huawei’s New Flagship Tablet: Beautiful and Responsive

Phil
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Huawei’s New Flagship Tablet: Beautiful and Responsive

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Huawei MatePad Pro 13.2 (2025): Key specifications

| CPU | Kirin T92 (octa-core) |
| Graphics | Malone 920 |
| Memory | 12GB |
| Storage | 512GB |
| Screen size | 13.2in |
| Screen type | Flexible OLED |
| Resolution | 2880 x 1920 |
| Max refresh rate | 144Hz |
| Rear cameras | 50MP f/1.8 (wide), 8 MP, f/2.2 (ultrawide) |
| Front camera | 16 MP, f/2.2 |
| OS | HarmonyOS 4.3 |
| Ports | USB 3.1 Type-C (DisplayPort 2.1) |
| Wireless connectivity | Wi-Fi, Bluetooth 5.2, Nearlink |
| Dimensions | 196 x 289 x 5.5mm |
| Weight | 580g |

Design and build

The first thing you’ll notice upon picking up the MatePad Pro is that it’s nice and light, especially compared to other 13-inch tablets such as the iPad Pro M1 we happened to have in the office at the same time. The next is the screen, which is a 16:9 OLED with Huawei’s lovely Papermatte coating that successfully cuts down on reflections.

Performance

We installed Microsoft Teams and Amazon Kindle as APKs, from two different download sources, and while Kindle worked OK, Teams wouldn’t sign in properly, which some might see as a blessing. The Geekbench app we use for comparing the performance of phones and tablets wouldn’t install at all, despite us downloading the APK twice, which is why there are no hard performance figures to accompany this review. The tablet’s CPU is hardly flagship-level, but it clearly has enough oomph in its eight cores to make the apps responsive, something helped by the 12GB of RAM.

Streaming video is patchily supported, at least by AppGallery apps. You can watch through the browser, and Disney+ appears in the form of a ‘Quick App’, which appears to be a Chromebook-style container for the web page, accessible from an icon but without downloading an APK. We were able to install Plex from AppGallery, Prime Video from an APK, and Disney+ as a Quick App. Netflix was nowhere to be seen, but worked through the browser. YouTube is available as a web app or through the browser.

Anything can run web apps. What we want from a £999 tablet is a smooth experience, and Huawei hasn’t quite got there yet, though it has improved. If you’re a heavy user of Google services then this isn’t the tablet for you, and CorelDraw Go wouldn’t work at all (the Edge browser looked like it was going to manage it, but errored after a while). The web version of Photoshop didn’t want to work in the mobile browser but would in Edge, while Photopea worked in all the browsers, and we were able to connect the MatePad to a mirrorless camera (though only one of the two memory card slots mounted, and it left some folders behind on the card) and to browse network storage with the Files app, so perhaps there’s hope for it yet if there’s a software update on the horizon – a desktop-class browser would be a big step.

Price

Priced at £999 at the time of writing, the Huawei MatePad Pro 13.2 is certainly cheaper than the 13in iPad Pro, which doesn’t come with a keyboard and stylus bundle but does have a more fully developed app ecosystem for creatives. The enormous 14.6-inch Samsung Galaxy Tab S10 Ultra costs more too, and both these tablets bring greater performance with them. Drop down to the 11-inch Google Pixel Tablet, however, and you’ll be paying a lot less.

Who is it for?

The Huawei MatePad Pro 13.2 isn’t really about processing power, but sells itself on the strength of its excellent screen. It’s pleasant to read, the papermatte coating cutting down on reflections. It’s nice to draw on, the bundled stylus feeling great against the screen. It’s also possible to use as an office machine thanks to the keyboard case and Microsoft 365 app compatibility. It’s a good all-rounder, but you have to put in a bit more work to get the apps you want than you would with other Android or Apple tablets.

Should I buy it?

Buy it if:

  • You want an all-round useful tablet with a great screen
  • You don’t mind apps being a bit of a fiddle
  • You don’t want to buy separate accessories

Don’t buy it if:

  • You’d rather have the full Android experience
  • Or an iPad
  • Or indeed a laptop

Also consider

  • The 11-inch Google Pixel Tablet
  • The 13in iPad Pro
  • The 14.6-inch Samsung Galaxy Tab S10 Ultra

1X will test humanoid robots in ‘a few hundred’ homes in 2025

Avery Winslow
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1X will test humanoid robots in ‘a few hundred’ homes in 2025

Norwegian Robotics Startup 1X Plans to Test Humanoid Robot in Homes

Early Tests

Norwegian robotics startup 1X plans to start early tests of its humanoid robot, Neo Gamma, in "a few hundred to a few thousand" homes by the end of 2025, according to the company’s CEO, Bernt Børnich.

"In recent months, the hype around humanoid robots for the home seems to have reached new heights."

Rise of Humanoid Robots

Figure, a Bay Area-based competitor to 1X with an active social media presence, announced in February that it would also begin home tests of its humanoid robots in 2025. Weeks later, Bloomberg reported Figure was in talks for a $1.5 billion fundraise at an eye-watering $40 billion valuation. OpenAI — a 1X investor — is also reportedly exploring building its own humanoid robots.

Challenges Ahead

However, putting heavy metal robots into peoples’ homes raises the stakes for the nascent industry. It’s not unlike autonomous vehicle startups putting their robotaxis on the road. It can turn south — quickly.

Limited Autonomy

However, Børnich is quite open about the fact Neo Gamma is a long way off from commercial scaling and autonomy. While Neo Gamma uses AI to walk and balance, the robot is not fully capable of autonomous movements today. To make in-home tests possible, Børnich says 1X is "bootstrapping the process" by relying on teleoperators — humans in remote locations that can view Neo Gamma’s cameras and sensors in real-time, and take control of its limbs.

Data Collection and Training

These in-home tests will allow 1X to collect data on how Neo Gamma operates in the home. Early adopters will help create a large, valuable dataset that 1X can use to train in-house AI models and upgrade Neo Gamma’s capabilities.

Privacy Concerns

Collecting data from microphones and cameras inside of people’s homes and then training AI models on it raises a whole host of privacy concerns, of course. In an email to TechCrunch, a company spokesperson said customers can decide when a 1X employee can view Neo Gamma’s surroundings — whether for auditing or teleoperation.

The Future of Humanoid Robots

Unveiled in February, Neo Gamma is the first bipedal robot prototype that 1X plans to test outside of the lab. Compared to Neo Beta, its predecessor, Neo Gamma features an improved onboard AI model, and a knitted nylon body suit that aims to reduce potential injuries from robot-to-human contact.

Conclusion

While a few hundred or thousand people might get to try an early, human-assisted version of Neo Gamma this year, it seems we’re still many years away from autonomous humanoid robots that you can just buy off the shelf.

FAQs

  • Q: How many homes will 1X test Neo Gamma in?
    A: A few hundred to a few thousand homes by the end of 2025.
  • Q: What is the current state of Neo Gamma’s autonomy?
    A: Neo Gamma is not fully capable of autonomous movements today.
  • Q: How will 1X collect and use data from in-home tests?
    A: 1X will collect data on how Neo Gamma operates in the home and use it to train in-house AI models and upgrade Neo Gamma’s capabilities.
  • Q: What are the privacy concerns surrounding 1X’s data collection practices?
    A: Collecting data from microphones and cameras inside of people’s homes and then training AI models on it raises a whole host of privacy concerns.

Enterprises Ignite Big Savings With NVIDIA-Accelerated Apache Spark

Emerson Blake
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Enterprises Ignite Big Savings With NVIDIA-Accelerated Apache Spark

Tens of thousands of companies worldwide rely on Apache Spark to crunch massive datasets to support critical operations, as well as predict trends, customer behavior, business performance and more. The faster a company can process and understand its data, the more it stands to make and save.

That’s why companies with massive datasets — including the world’s largest retailers and banks — have adopted NVIDIA RAPIDS Accelerator for Apache Spark. The open-source software runs on top of the NVIDIA accelerated computing platform to significantly accelerate the processing of end-to-end data science and analytics pipelines — without any code changes.

To make it even easier for companies to get value out of NVIDIA-accelerated Spark, NVIDIA today unveiled Project Aether — a collection of tools and processes that automatically qualify, test, configure and optimize Spark workloads for GPU acceleration at scale.

Project Aether Completes a Year’s Worth of Work in Less Than a Week

Customers using Spark in production often manage tens of thousands of complex jobs, or more. Migrating from CPU-only to GPU-powered computing offers numerous and significant benefits, but can be a manual and time-consuming process.

Project Aether automates the myriad steps that companies previously have done manually, including analyzing all of their Spark jobs to identify the best candidates for GPU acceleration, as well as staging and performing test runs of each job. It uses AI to fine-tune the configuration of each job to obtain the maximum performance.

To understand the impact of Project Aether, consider an enterprise that has 100 Spark jobs to complete. With Project Aether, each of these jobs can be configured and optimized for NVIDIA GPU acceleration in as little as four days. The same process done manually by a single data engineer could take up to an entire year.

CBA Drives AI Transformation With NVIDIA-Accelerated Apache Spark

Running Apache Spark on NVIDIA accelerated computing helps enterprises around the world complete jobs faster and with less hardware compared with using CPUs only — saving time, space, power and cooling, as well as on-premises capital and operational costs in the cloud.

Australia’s largest financial institution, the Commonwealth Bank of Australia, is responsible for processing 60% of the continent’s financial transactions. CBA was experiencing challenges from the latency and costs associated with running its Spark workloads. Using CPU-only computing clusters, the bank estimates it faced nearly nine years of processing time for its training backlog — on top of handling already taxing daily data demands.

"With 40 million inferencing transactions a day, it was critical we were able to process these in a timely, reliable manner," said Andrew McMullan, chief data and analytics officer at CBA.

Running RAPIDS Accelerator for Apache Spark on GPU-powered infrastructure provided CBA with a 640x performance boost, allowing the bank to process a training of 6.3 billion transactions in just five days. Additionally, on its daily volume of 40 million transactions, CBA is now able to conduct inference in 46 minutes and reduce costs by more than 80% compared with using a CPU-based solution.

Global Ecosystem

RAPIDS Accelerator for Apache Spark is available through a global network of partners. It runs on Amazon Web Services, Cloudera, Databricks, Dataiku, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure.

Dell Technologies today also announced the integration of RAPIDS Accelerator for Apache Spark with Dell Data Lakehouse.

Conclusion

In conclusion, Project Aether and NVIDIA-accelerated Apache Spark are revolutionizing the way companies process and analyze massive datasets. With the ability to automate GPU acceleration at scale, companies can expect significant performance gains, reduced costs, and faster time-to-insight.

FAQs

Q: What is Project Aether?
A: Project Aether is a collection of tools and processes that automatically qualify, test, configure and optimize Spark workloads for GPU acceleration at scale.

Q: How does Project Aether work?
A: Project Aether analyzes all Spark jobs to identify the best candidates for GPU acceleration, stages and performs test runs of each job, and uses AI to fine-tune the configuration of each job to obtain the maximum performance.

Q: What is RAPIDS Accelerator for Apache Spark?
A: RAPIDS Accelerator for Apache Spark is a collection of open-source software that runs on top of the NVIDIA accelerated computing platform to accelerate the processing of end-to-end data science and analytics pipelines.

Q: Where can I get RAPIDS Accelerator for Apache Spark?
A: RAPIDS Accelerator for Apache Spark is available through a global network of partners, including Amazon Web Services, Cloudera, Databricks, Dataiku, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure.

MONAI: Multimodal Medical AI Ecosystem

Jordan Waverly
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MONAI: Multimodal Medical AI Ecosystem

MONAI Multimodal: Bridging Healthcare Data Silos

The growing volume and complexity of medical data—and the pressing need for early disease diagnosis and improved healthcare efficiency—are driving unprecedented advancements in medical AI. Among the most transformative innovations in this field are multimodal AI models that simultaneously process text, images, and video. These models offer a more comprehensive understanding of patient data than traditional, single-modality systems.

MONAI, the fastest-growing open-source framework for medical imaging, is evolving to integrate robust multimodal models that are set to revolutionize clinical workflows and diagnostic precision. Over the past five years, MONAI has become a leading medical AI platform and the de facto framework for imaging AI research. It has more than 4.5 million downloads and appears in more than 3,000 published papers.

MONAI Multimodal: Bridging Healthcare Data Silos

As medical data becomes more varied and complex, the need for comprehensive solutions that unify disparate data sources has never been greater. MONAI Multimodal represents a focused effort to expand beyond traditional imaging analysis into an integrated research ecosystem. It combines diverse healthcare data—including CT and MRI, as well as EHRs and clinical documentation—to drive research development and innovation in radiology, surgery, and pathology domains.

Key enhancements include:

  • Agentic AI Framework: Uses autonomous agents for multi-step reasoning across images and text
  • Specialized LLMs and VLMs: Tailored models designed for medical applications that support cross-modal data integration
  • Data IO components: Integrates diverse data IO readers, including DICOM, EHR, video, WSI, and text

MONAI Multimodal Building Blocks for a Unified Medical AI Research Platform

As part of the broader initiative, the MONAI Multimodal Framework comprises several core components designed to support cross-modal reasoning and integration.

Agentic Framework

The agentic framework is a reference architecture for deploying and orchestrating multimodal AI agents that enable multistep reasoning by integrating image and text data with human-like logic. It supports custom workflows through customizable, agent-based processing and reduces integration complexity by bridging vision and language components effortlessly.

Hugging Face Integration

Standardized pipeline support connecting MONAI Multimodal with Hugging Face research infrastructure:

  • Model sharing for research purposes
  • Integration of new models
  • Broader participation in the research ecosystem

Community-Led Partnerships

Community-led partner models include:

  • RadViLLA: Developed by Rad Image Net, The BioMedical Engineering and Imaging Institute at Mount Sinai’s Icahn School of Medicine, and NVIDIA, RadViLLA is a 3D VLM for radiology that excels in responding to clinical queries for the chest, abdomen, and pelvis.
  • CT-CHAT: Developed by the University of Zurich, CT-CHAT is a cutting-edge vision-language foundational chat model specifically designed to enhance the interpretation and diagnostic capabilities of 3D chest CT imaging.

Build the Future of Medical AI with MONAI Multimodal

MONAI Multimodal represents the next evolution of MONAI, the leading open-source platform for medical imaging AI. Building on this foundation, MONAI Multimodal extends beyond imaging to integrate diverse healthcare data types—from radiology and pathology to clinical notes and EHRs.

Through a collaborative ecosystem of NVIDIA-led frameworks and partner contributions, MONAI Multimodal delivers advanced reasoning capabilities through specialized agentic architectures. By breaking down data silos and enabling seamless cross-modal analysis, the initiative addresses critical healthcare challenges across specialties, accelerating both research innovation and clinical translation.

Conclusion

MONAI Multimodal is transforming healthcare—empowering clinicians, researchers, and innovators to achieve breakthrough results in medical imaging and diagnostic precision. By unifying diverse data sources and leveraging state-of-the-art models, MONAI Multimodal is breaking down barriers and fostering collaboration across the medical AI community.

FAQs

Q: What is MONAI Multimodal?
A: MONAI Multimodal is an open-source framework for medical AI that integrates diverse healthcare data types and enables seamless cross-modal analysis.

Q: What are the key features of MONAI Multimodal?
A: MONAI Multimodal features an agentic framework, specialized LLMs and VLMs, and data IO components.

Q: What are the benefits of using MONAI Multimodal?
A: MONAI Multimodal enables advanced reasoning capabilities, breaks down data silos, and accelerates research innovation and clinical translation.

Q: Who is behind MONAI Multimodal?
A: MONAI Multimodal is an NVIDIA-led initiative, with contributions from partner organizations and research institutions.

Q: How can I get started with MONAI Multimodal?
A: Join us at NVIDIA GTC 2025 and check out the related sessions.

SwitchBot Adds Robot Vacuums, Smart Shades, and Its New Hub 3 to Home Assistant

Avery Winslow
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SwitchBot Adds Robot Vacuums, Smart Shades, and Its New Hub 3 to Home Assistant

SwitchBot to Integrate Over 45 Devices with Home Assistant by Mid-Year

Wider Support for Home Assistant Users

SwitchBot, a company specializing in smart home products, has announced that it will integrate more than 45 of its products with the open-source Home Assistant platform by the end of the first half of this year. This expansion includes the recently revealed SwitchBot Hub 3, which was first filed with the Connectivity Standards Alliance last week.

April Delivers the Goods

Many of these integrations are expected to arrive in April, according to a list on SwitchBot’s website, which includes the Robot Vacuum K10 Plus Pro, Curtain 3 smart shades, and its garage door opener. These devices will join other SwitchBot products that already have Home Assistant integration, such as the SwitchBot Lock Pro.

Stability and Community Benefits

Given SwitchBot’s diverse and ever-growing collection of smart home products, its commitment to integrating so many devices is great news for users of the open-source Home Assistant platform. The community-created integrations that allow devices from major smart home players to work with Home Assistant can be fragile, as companies make undocumented software adjustments or actively try to prevent those integrations from working at all.

Conclusion

This integration will provide a more seamless experience for users, allowing them to control and monitor their smart home devices from a single platform. With SwitchBot’s expanded support for Home Assistant, users can expect improved compatibility and reduced complexity in their smart home setup.

Frequently Asked Questions

Q: What products will be integrated with Home Assistant?
A: Over 45 SwitchBot products, including the Robot Vacuum K10 Plus Pro, Curtain 3 smart shades, and its garage door opener, among others.

Q: When can I expect these integrations?
A: Many of the integrations will be available in April, with the rest expected to follow throughout the year.

Q: Why is this important for Home Assistant users?
A: This expansion provides a more comprehensive and stable experience for users, allowing them to control and monitor their smart home devices from a single platform.

The Simplicity Paradox

Parker Lennox
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The Simplicity Paradox

Serving the Revolution to Low-Tech Users

Modern technology is supposed to make our lives easier, but sometimes it feels like it is actually making things inaccessible to those who need it most. Sometimes it hides the simple pleasures of life and distracts us from them. Modern tools demand a level of technical fluency that only engineers and enthusiasts will comfortably navigate, leaving the rest of the world to either struggle or opt out entirely.

But true innovation isn’t about adding complexity — it’s about making complexity invisible.

Serving the Revolution to Low-Tech Users

Right now, technology is designed by engineers, for technophiles. Even when companies claim to focus on “user experience,” they’re usually just smoothing out the edges of already complex systems rather than rethinking how those systems could serve people with minimal technical literacy. There is now a ton of opportunity to serve those people.

The Role of AWS and Serverless in Invisible Tech

The beauty of serverless computing is that it allows us to build high-powered applications with lightweight, accessible interfaces. AWS already provides many of the building blocks to create seamless, invisible tech experiences:

  • Amazon Lex & Polly – AI-driven voice interaction that can make services available through simple phone calls
  • AWS Lambda – Event-driven, scalable backend logic without infrastructure concerns
  • Amazon Connect – Cloud-based call centers that could act as automated helpers for people who struggle with traditional apps
  • API Gateway & Step Functions – A way to chain together complex logic without forcing the user to navigate it

With these tools, we could build systems that let people interact with powerful tech using only voice commands, phone calls, or simple text input—no apps, no accounts, no friction.

Invisible Tech Improvements for Underserved Communities

Drawing from my recent experiences training as an EMT, I’ve encountered various individuals—particularly older adults, people battling substance use disorders, those managing pain, and those suffering from chronic conditions. Many of these individuals have minimal familiarity with complex technologies, yet their need for accessible, intuitive tech is deep.

Imagine how invisible tech could make an impact in underserved communities:

  • Accessibility-First Interfaces for Low-Sight Users: Empowering tool: Imagine a purpose-built interface specifically designed for individuals with low or no sight. This could involve voice-activated and haptic feedback systems that guide the user through an app’s functions without requiring any visual interaction.
  • Algorithmic Content Customization for Accessibility: Empowerment tool: For individuals with sight limitations, an algorithm-based content stream could be designed to serve them better. For example, an app that curates their own calendar and task list over time to generate streams of upcoming events and todo items combined to give them a verbal/audio map of the possible day ahead for based on their calendar, their task list, and also algorithmically adjusting to their preferences over time and individualized specifically to what is happening with them.
  • Emergency and Health Monitoring via Voice: Empowerment tool: A voice-activated system designed for individuals with health concerns could integrate with wearables and sensors to allow users to request help, check vitals, or even get emergency instructions without needing to touch anything.
  • Simple Communication Tools for Substance Recovery Patients: Empowerment tool: A low-barrier communication platform, like a voice-activated chatbot or a very simplified text interface, could allow these individuals to easily check in with healthcare providers, support groups, or have scheduled check-ins with family members.

Building for Outcomes, Not Just Implementation

As engineers, it’s easy to get obsessed with the underlying machinery—optimizing APIs, tweaking performance, debating monoliths vs. microservices. But none of that matters if the end result isn’t usable by real people.

The real question isn’t how something is built—it’s who it’s built for. The best technology serves people without them ever needing to think about it.

Footnotes

Footnote 1: Yes, I understand there’s a danger to hiding all that complexity. When we hide the complexity of a thing we get perverse outcomes. Even the example of someone using complex neural network technology and artificial intelligence to get a pecan pie recipe could be considered a counterexample, and a negative result. I still personally do that sometimes, I ask ChatGPT for a pie recipe that I could google… There is also the subtle side effect of how when you use AI and an LLM to get a pecan pie recipe, it decreases the incentive for someone out there on the Internet to write that pecan pie recipe in the first place. I leave these two problems as out of scope, for others far smarter than I to solve.

FAQs

Q: What is invisible tech?
A: Invisible tech refers to technology that is designed to be easy to use and accessible to everyone, regardless of their technical background or ability.

Q: How can we make technology more accessible?
A: By designing technology that is simple, intuitive, and easy to use, we can make it more accessible to people who may not be familiar with complex technologies.

Q: What is the role of AWS and serverless computing in invisible tech?
A: AWS and serverless computing can play a crucial role in invisible tech by providing the building blocks for building high-powered applications with lightweight, accessible interfaces.

Q: Who benefits from invisible tech?
A: Invisible tech can benefit a wide range of people, including older adults, people with disabilities, and those who may not be familiar with complex technologies.

5 Signs You Need One

Parker Lennox
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5 Signs You Need One

How to Identify if Your Business Needs AI Agents

Have you ever wondered how businesses are handling complex tasks with ease? In fact, 60% of businesses now use AI to boost productivity. As we approach 2025, the demand for AI agents for business is growing rapidly. 

These smart tools are transforming AI agents industries, from automating customer service to predicting market trends. But how do you know if your business needs one?

If you’re struggling with scaling operations or making sense of your data, AI agent development tools might be the solution you need. Whether you’re looking to improve customer experience or gain better insights into market behavior, training AI models to fit your needs can take your business to the next level. AI agents for growth are essential for business success. 

AI agents for growth are no longer just for large companies, small businesses are benefiting too. In this article, we’ll check up on 5 key signs you business calls for AI agent. 

Stay ahead by integrating AI into your operations for automation and efficiency. Start your project now!

What are AI Agents?

AI agents are smart tools that help businesses automate tasks and make decisions. These agents use artificial intelligence to understand and process data, improving efficiency.

AI agents are systems designed to perform tasks like a human would but with the power of AI. They can learn, adapt, and make decisions.

Examples:

  • Chatbots: Handle customer inquiries and provide instant responses.
  • Virtual Assistants: Like Siri, Google Assistant, or Alexa, they help manage schedules.
  • Predictive Analytics Tools: Forecast trends and customer behavior.
  • Automated Workflow Systems: Automate repetitive tasks in business operations.

By 2025, AI agents for business will be essential. The rapid evolution of AI tools, like AI agents for growth, means businesses must adapt or fall behind. Companies already using AI agents for business have seen an increase in productivity.

5 Signs Your Business Needs an AI Agent

In the fast-paced business world, staying ahead is crucial. AI agent development for businesses helps streamline operations and enhance customer service. 

Training AI models tailor AI agents to your business needs, improving efficiency and reducing team workload.

1. Overwhelmed Customer Support Team

Sign: 

Long response times, high ticket volumes, and customer complaints about service delays.

Customer service is one of the most critical aspects of any business. But what happens when the volume of customer queries becomes overwhelming? 

Research shows that 60% of customers expect a response within an hour of sending an inquiry. If your team is struggling to meet these demands, it’s time to consider AI agents for business.

Solution: 

AI agents can handle routine inquiries, freeing up your team to focus on more complex issues. These AI agents can be trained to provide 24/7 support, reducing the need for extensive human intervention.

Conclusion

Adopting AI agents for business can help streamline operations and boost growth. As we’ve discussed, businesses need to assess their needs, research AI solutions, and choose a reliable provider for successful integration. 

AI agents for growth are essential for enhancing customer service, marketing, and operations. With the right AI agent development tools, you can ensure that AI supports your business goals and improves productivity. 

FAQs

What are AI agents for business?

AI agents for business automate tasks like customer service, marketing, and operations to improve efficiency.

How can AI agents help my business grow?

AI agents for growth can streamline processes and boost productivity, saving time and resources.

What are the benefits of using AI tools for business?

AI agent development tools help businesses improve decision-making, automate tasks, and stay competitive.

How do I start using AI agents?

Start by assessing your business needs, researching solutions, and partnering with an expert AI provider like LITSLINK.

Can AI agents handle customer service?

Yes, AI agents for business can effectively manage customer queries, improving response times and satisfaction.

Deepfake Detection Now Free for All Users

Emerson Blake
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Deepfake Detection Now Free for All Users

Deepfake Detection Service Loti AI Expands Access to All Users for Free

Introduction

The rise of AI-generated hyper-realistic visual and audio deepfakes on the internet has raised concerns about how public figures and celebrities’ likenesses are used without their consent to produce content. Loti AI, a deepfake detection firm, entered the scene in 2022 to help safeguard and protect public figures against AI-generated content and has now expanded its services.

Loti AI’s "Human-First" Likeness Protection Technology

On Wednesday, Loti AI announced that its "human-first" likeness protection technology will be available to all users. Previously only offered to public figures and celebrities, the company will now provide tools to anyone interested in protecting their digital reputation. Deepfakes are videos, speech, or images in which the actor or action is not real but created by AI, making distinguishing between real and fake content challenging.

How Loti AI’s Platform Works

Loti AI’s platform scans the internet daily for deepfakes, adult content, impersonations, unauthorized content, and even authentic images being misused. The firm’s likeness protection technology uses a custom-built filtering system to safeguard users’ digital identity by removing fake content with "four simple steps":

Steps to Protect Your Digital Reputation

  • Step 1: Authorize – Users must complete a quick likeness check to verify their identities to ensure they are the person they claim to be.
  • Step 2: Find – Users must provide scans of their face and voice for matching and identity protection.
  • Step 3: Remove – Users choose what content they’d like removed from the internet, and Loti will conduct automated takedowns.
  • Step 4: Protect – Loti provides 24/7 monitoring, automated likeness protection, and weekly scan updates. Users can also opt to take down the fake content manually.

Results and Statistics

According to the company, users who opted into its auto-takedown functionality saw a 95% takedown rate within 17 hours. Loti AI offers free and paid membership options on a rolling basis. To get started, potential users must sign up for the waitlist at lotiai.com/sign-up or download the Loti AI app on iOS/Android.

Conclusion

The internet is getting out of hand, and people’s digital reputations are at risk like never before. Loti AI’s goal is simple: to help you reach zero images of you online that you haven’t approved.

Frequently Asked Questions

Q: How does Loti AI’s likeness protection technology work?
A: Loti AI’s platform uses a custom-built filtering system to safeguard users’ digital identity by removing fake content with four simple steps: Authorize, Find, Remove, and Protect.

Q: Is Loti AI’s service only for public figures and celebrities?
A: No, Loti AI’s service is now available to all users, not just public figures and celebrities.

Q: How do I get started with Loti AI’s service?
A: Potential users must sign up for the waitlist at lotiai.com/sign-up or download the Loti AI app on iOS/Android.

Q: Is Loti AI’s service free?
A: Loti AI offers free and paid membership options on a rolling basis.

Meta Spotted Testing AI-Generated Comments on Instagram.

Avery Winslow
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Meta Spotted Testing AI-Generated Comments on Instagram.

Meta Tests AI-Generated Comments on Instagram

Introducing AI-Generated Comments on Instagram

In a recent move, Meta has introduced a new feature that uses AI to facilitate interactions between friends by helping them write comments on Instagram. The feature, which is currently being tested, suggests three AI-generated comments for users to choose from when they want to leave a comment on a post.

How it Works

According to a video posted by user Jonah Manzano, who often tests new social media features, the "Write with Meta AI" prompt is available on Instagram. When users tap on the prompt, Meta AI analyzes the photo and generates three suggestions for comments. For example, if the photo is of someone smiling with a thumbs-up in their living room, Meta AI suggests comments like "Cute living room setup," "Love the cozy atmosphere," or "Great photo shoot location." If users don’t like the first three suggestions, they can refresh to get more.

Test Feature Availability

Meta did not provide any details on the test feature’s availability, but the company noted that it tested AI-generated comments on Facebook last year. It’s unclear when or if the feature will be rolled out more widely.

User Reactions

The new feature has received mixed reactions from users, with some welcoming the idea of AI-generated comments and others expressing concerns about the authenticity and originality of the content. Many users yearn for the days when Instagram was more authentic and there wasn’t as much pressure to perform, so the addition of AI comments could be deemed inauthentic and unnecessary.

Conclusion

The introduction of AI-generated comments on Instagram is just the latest example of Meta’s efforts to leverage AI in its apps. While the feature may be seen as a convenient shortcut for some users, others may be concerned about the impact on the authenticity of online interactions.

FAQs

Q: Will AI-generated comments be available on all Instagram posts?
A: No, the feature is currently being tested and its availability is unclear.

Q: How do I access the AI-generated comments feature?
A: The feature is currently available for some users, but Meta has not provided details on how to access it.

Q: Will AI-generated comments be available on other Meta apps?
A: Meta has tested AI-generated comments on Facebook last year, but it’s unclear if the feature will be rolled out on other apps.

Q: Can I opt-out of the AI-generated comments feature?
A: It’s not clear if users will have the option to opt-out of the AI-generated comments feature.

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