China’s “AI Hospital” Revolution: What It Is, How It Works, And The Questions It Raises

 What Will Doctors Do?

China has moved fast from AI-assisted tools to whole systems that replicate clinical workflows. In 2024–25, researchers and companies unveiled large-scale “AI hospital” projects that use agent-style AI doctors, virtual patients, and hospital automation to diagnose, triage and follow up with patients at speeds no human team could match. These developments promise greater access and efficiency in a health system facing doctor shortages, but they also raise urgent questions about safety, regulation and real-world clinical value.

What is the “AI hospital”?

The name covers a family of initiatives rather than one single building. Tsinghua University’s Institute for AI Industry Research (AIR) created an “Agent Hospital” platform in which AI agents simulate the full patient journey — from symptom onset to triage, consultation, prescription and follow-up — using large language and domain models and synthetic patient datasets.

The system was initially described as operating with a small cohort of AI “doctors” and nurses and later expanded to dozens of specialist agents covering 20+ clinical areas and hundreds of disease scenarios. Developers report very high benchmark performance on medical question sets and the ability to simulate and “treat” thousands of virtual patients in a short time.

How the technology is being deployed?

Beyond Tsinghua’s lab environment, commercial AI stacks such as DeepSeek-R1 and vendor systems from cloud and tech firms have been piloted across hundreds of hospitals. DeepSeek’s models, promoted as low-cost and highly capable, were rapidly integrated into diagnostic, administrative and imaging workflows across many tertiary hospitals, and academic preprints describe local deployment at scale. Other pilots have focused on AI-powered triage, precision checkups and automated follow-up systems that aim to reduce routine clinician workload. These deployments are increasingly supported by cloud providers and local health authorities.

Claims and early results

Project teams and some coverage highlight striking numbers: diagnostic accuracy figures cited around 93% on medical QA benchmarks and simulations that “process” thousands of cases in days. Tsinghua’s Agent Hospital and allied spin-outs have released figures about the number of AI agents, covered specialties and synthetic datasets used to train and stress-test systems. Early pilots suggest large gains in throughput for tasks like automated histories, follow-up calls and image pre-screening.

Concerns from clinicians and researchers

Rapid rollout has triggered scepticism. Clinicians and safety researchers warn that benchmark performance and simulated-case throughput do not necessarily translate to safe, generalizable clinical care for diverse real-world patients. Critics point to risks such as hallucinated or incorrect recommendations, bias from training data, lack of transparent audit trails, and the challenge of integrating AI decisions with complex human judgment. Several commentaries and academic voices argue that deployment has outpaced independent validation and regulatory oversight.

Regulatory and policy context

China’s central and local governments have signalled strong support for AI in healthcare as a national priority, enabling rapid trials and procurement. That political backing, combined with the availability of powerful domestic models and cloud infrastructure, has let projects scale quickly. Observers note that the speed of adoption makes it especially important for regulators, hospitals and vendors to define responsibilities, clinical evaluation standards, data governance rules and patient-consent frameworks.

What to watch next?

Key indicators of whether these AI hospitals become safe, useful fixtures will be independent clinical trials, peer-reviewed evaluations against real-patient outcomes, transparent auditing of errors, and clear regulatory standards for deployment. If China’s experiments produce robust evidence of benefit and safety, they could reshape clinical workflows worldwide; if not, they will serve as a cautionary tale about technology outpacing validation. Either way, the AI hospital story underscores that transforming healthcare at scale requires not only powerful models but also careful clinical governance.

Tags: AI hospital, AI doctors, virtual patients, Tsinghua University’s Institute for AI Industry Research (AIR), Agent Hospital, nurses, DeepSeek-R1

Bigg Boss 19: Nagma Mirajkar’s Exit From Show Serves As A Reality Check For Influencers

Stepping into the Bigg Boss 19 house is often seen as a golden chance for celebrities and influencers to showcase their personality beyond social media. For Nagma Mirajkar, who commands an impressive following of more than eight million, this was supposed to be her moment to shine. 

Yet, just weeks into the show, she was evicted, leaving fans and viewers puzzled. Even the fact that her partner, Awez Darbar, has over thirty million followers did little to help her survive in the competition.

On the popular Weekend Ka Vaar episode, Nagma was among the first contestants asked to leave the house, alongside actor Natalia Janoszek. Natalia’s struggle was clear since the language barrier kept her from fully engaging, but in Nagma’s case, the issue was different—she was barely visible on the show. For someone who built her career on constant visibility and engagement with fans, this was unexpected.

Nagma’s journey as an influencer has been noteworthy. She was one of the earliest creators to make a smooth transition from TikTok to Instagram after the platform was banned in India. Her collaborative dance videos with her partner, choreographer Awez Darbar, made her popular, and she later expanded into makeup tutorials, travel content, and personal vlogs on YouTube. 

With such a wide digital presence, the show offered her a chance to connect not only with her own audience but also with Awez’s large fanbase. She even had the support of Bigg Boss 7 winner Gauahar Khan, who she admired deeply. Before entering the house, Nagma had shared how she remembered Gauahar’s victory and dreamed of holding the trophy herself someday. Gauahar had advised her to simply be authentic and play her own game rather than trying to imitate others.

However, once inside the house, Nagma failed to leave a mark. She had nearly three weeks to show her personality and strategy, but she chose to remain silent in most situations. Whether it was disagreements in the kitchen, heated debates about nominations, or even while moderating a task assigned to her, she avoided taking a stand. For a reality show that thrives on opinions, clashes, and strong presence, her quiet approach did not work. To many loyal viewers, it seemed like she was just another face in the background rather than an active participant.

This lack of involvement was particularly disappointing because influencers have increasingly used Bigg Boss as a stage to boost their careers. Elvish Yadav, a popular content creator from Gurgaon, is one of the best examples. He entered as a wild card contestant in the OTT version of the show and went on to become the first ever wild card winner. After his victory, he continued to shine on television, winning MTV Roadies XX as a gang leader and Laughter Chefs Season 2. His success wasn’t accidental—he made sure to be visible, engaged, and strategic in the house, showing the kind of energy viewers expect from a winner.

Other influencers like Abhishek Malhan, Sunny Arya, Anurag Dobhal, Armaan Malik with his two wives Kritika and Payal, and Lovekesh Kataria also made their presence felt during different seasons. Their outcomes varied, but they all ensured that they brought something to the table, whether through drama, opinions, or entertainment value.

Nagma’s elimination, despite her huge social media following, highlights an important truth about Bigg Boss: numbers outside the house don’t matter if you don’t play the game inside it. The audience wants contestants who bring life, conflict, and personality to the show. Without that, even millions of followers can’t guarantee survival in the house.

Tags: Bigg Boss 19, BB19, Nagma Mirajkar, Natalia Janoszek, Awez Darbar, TikTok, Instagram

7 Ways Small Businesses Can Use Artificial Intelligence Without Breaking the Bank

Practical, low-cost AI strategies that boost efficiency, marketing and customer service for small businesses.

Small businesses can get big benefits from affordable AI tools without blowing their budgets. By focusing on practical, low-cost AI uses—like automating customer support, speeding up content creation, and simplifying routine workflows—owners can free time, cut costs, and improve customer experience. This guide highlights seven budget-friendly ways small businesses can use AI, with concrete tool types and tips to start on free or low-cost plans. Whether you’re a solo founder or a tiny team, these strategies will help you adopt AI step-by-step and measure ROI, so you use intelligent automation to grow revenue rather than inflate expenses.

Also read: HowArtificial Intelligence (AI) Tools Are Quietly Changing the Way We Work EveryDay?

The business landscape is changing fast. Adoption of generative and business AI surged in recent years, with a major jump in corporate usage between 2023 and 2024, a sign that even small operations can no longer ignore practical AI if they want to stay competitive. Start smart: test one small AI use-case, measure impact, then scale.

1) Automate basic customer support with chatbots and AI replies:

Set up an AI-powered chatbot for FAQs and simple customer queries so your team only handles complex issues. Many chatbot platforms offer free or low-cost tiers that plug into websites and WhatsApp or Messenger. Using AI for first-level support reduces wait times and lowers staffing costs. Start with rule-based flows plus a light generative-AI fallback for off-script questions; measure how many conversations the bot resolves before handing off to a human. Free or entry-level ChatGPT or similar chatbot integrations are often enough for early experiments.

2) Produce marketing content faster with AI writing tools:

Rather than hiring expensive freelance writers for every blog, social post, or product description, use AI writing assistants to draft and ideate. Tools like Canva’s Magic Write or entry-level ChatGPT plans help produce headlines, captions, email copy, and product blurbs quickly then you or a human editor polishes the final version. This slashes drafting time and lets you publish more consistently. Use free quotas first and move to paid plans only if the volume justifies the spend.

3) Improve email and ad performance with AI optimization:

AI can suggest subject lines, A/B test ad copy, and optimize send times. Small businesses can plug AI suggestions into low-cost email platforms or use add-ons that analyze past campaigns to boost open and conversion rates. Rather than replacing your marketer, use AI to generate variants and predictions, then run inexpensive A/B tests to confirm which changes actually increase revenue.

4) Create visuals and short videos affordably:

Design tools with AI templates let non-designers produce polished visuals and short videos without hiring an agency. Canva and similar platforms include AI-driven layout, image, and text tools that are available on free or affordable Pro plans—perfect for social ads, product posts, or quick explainer clips. For short localized video content, newer AI video startups offer pay-as-you-go options rather than big subscriptions. Use templates and batch-create content to maximize ROI.

5) Automate repetitive workflows with no-code tools:

Connect form submissions, invoices, CRMs, and email lists with automation tools so your team spends less time copying data. No-code platforms like Zapier provide free and low-cost tiers that let small businesses build automations across the apps they already use. Start with a couple of “zaps” that save time every day—then track how many hours they free up. This often pays back the subscription in improved productivity within weeks.

6) Smarter sales and lead management using AI features in CRMs:

Modern CRMs embed AI features—lead scoring, summarized call notes, and suggested next steps—that help small sales teams close deals faster. Many CRM vendors have entry-level or free plans that include some AI features; even simple scoring helps prioritize follow-ups so your small team focuses on high-value leads. Pair AI insights with a disciplined sales process to turn smarter data into real wins.

7) Use AI for quick analytics and decision-making:

AI can summarize dashboards, flag anomalies, and translate raw numbers into plain-language recommendations. Instead of hiring a data analyst, use built-in AI assistants in your analytics or spreadsheet tools to get insights and “what-if” scenarios. For example, AI features in office and productivity suites help turn sales and inventory data into priorities—saving time and reducing costly mistakes. Consider tools with integrated Copilot-style assistants if your budgeting allows, but begin with lighter, free analytics add-ons.

Practical tips to adopt AI without overspending:

Begin small, limit pilots to one department, and use free tiers to test value. Track direct metrics (time saved, conversion lift, reduced ticket volume) so you know whether to upgrade. Pay attention to data privacy and vendor terms when putting customer data into third-party AI tools. Finally, combine AI outputs with human review—AI should amplify your team, not replace judgment.

Affordable AI isn’t about expensive enterprise licenses; it’s about picking targeted use-cases, leveraging free and low-cost tiers, measuring impact, and scaling what works. For small businesses, even small automations and smarter content workflows can produce outsized benefits in speed, consistency, and customer satisfaction. Start with one of the seven approaches above, measure results, and reinvest savings into the next AI improvement.

Tags: small businesses, affordable AI tools, use AI, AI for small business, AI automation, budget AI solutions, low-cost AI marketing.

Bigg Boss 19: Amaal Mallik Accuses Awez Darbar Of Cheating Girlfriend Nagma Mirajkar

Baseer Ali also supported Mallik

In the latest episode of Bigg Boss 19, contestants Amaal Mallik and Baseer Ali stirred controversy by making allegations about fellow housemate Awez Darbar.

They claimed that Awez has been unfaithful to his long-time girlfriend, Nagma Mirajkar, who is also part of the show this season.

Also read: Bigg Boss 19- Awez Darbar Opens Up On Being Cheated By Ex,“Jitne Dost The, Sabse….”

Baseer hinted that he knew many details about Awez’s private life and accused him of seeking attention from multiple women outside his relationship. Amaal supported these claims, suggesting that Awez frequently messages other girls on social media, despite being in a committed relationship for nearly a decade.

The situation escalated after a heated argument between Awez and Baseer during a captaincy task. Baseer warned Awez to play fairly, even threatening to reveal more personal details if the fight continued.

Also read: Tanya Mittal Becomes Most Talked-About & Most Trending Contestant On Day One

Bigg Boss 19 features several well-known personalities including Gaurav Khanna, Ashnoor Kaur, Mridul Tiwari, Kunickaa Sadanand, Abhishek Bajaj, Tanya Mittal, Zeishan Quadri, Nehal Chudasama, Natalia Janoszek, Pranit More, Farhana Bhatt, and Neelam Giri. Hosted by Salman Khan, the show is available on JioHotstar and Colors TV.

Tags: Bigg Boss 19, BB19, Amaal Mallik, Awez Darbar, Nagma Mirajkar, Baseer Ali