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MedLM by Google is Transforming the Healthcare Industry

MedLM: A Healthcare-Focused AI Model by Google

In the realm of healthcare, the use of Artificial Intelligence (AI) has been transformative, with AI models playing a crucial role in various tasks. However, the complexity and volume of healthcare data present unique challenges. This is where Google’s MedLM model steps in, providing a solution that is specifically designed for the healthcare industry.

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Architecture of MedLM

The architecture of MedLM is based on Google’s Large Language Models (LLMs). It’s powered by Med-PaLM 2, a research model that achieves human expert-level performance on the USMLE and generates comprehensive, helpful answers to consumer health questions.

MedLM Models

MedLM is currently composed of two models, each with its own strengths and ideal use cases:

1. MedLM-medium

MedLM-medium provides customers with better throughputs and includes more recent data. 

2. MedLM-large

MedLM-large is the same model from the preview phase. Both models will continue to be refreshed over the product lifecycle.

Both models have separate endpoints and provide customers with additional flexibility for their use cases.

Intended Usage

MedLM is designed with the following intended uses in mind:

1. Clinical Decision Support

Assisting healthcare professionals in analyzing patient data, suggesting diagnoses and treatment options, and identifying potential complications.

2. Personalized Medicine

Tailoring treatment plans and medication recommendations to individual patients based on their unique characteristics and genetic information.

3. Medical Research and Development

Accelerating research efforts by analyzing large datasets of medical literature and clinical trial data, identifying promising drug targets, and generating new research hypotheses.

4. Patient Education and Engagement

Providing patients with personalized and understandable educational materials based on their diagnoses and medical history, improving adherence to treatment plans and overall healthcare literacy.

5. Enhanced Medical Practice Efficiency

Automating routine tasks like medical report generation and data analysis, freeing up healthcare professionals’ time for patient care.

6. Public Health and Accessibility

Providing virtual medical assistants, facilitating access to accurate medical information, and translating medical documents for diverse populations.

MedLM in Action

MedLM, Google’s healthcare-focused AI model, is transitioning from theoretical potential to practical application. Here are some exciting real-world pilots showcasing their impact:

1. Streamlining Clinical Documentation

HCA Healthcare, a US healthcare giant, is collaborating with Augmedix to leverage MedLM for automated medical note generation. This translates physician-patient conversations into draft notes in real-time, boosting efficiency, reducing burnout, and potentially scaling across specialities.

2. Accelerating Drug Discovery

BenchSci, a biotech research platform, is integrating MedLM into its ASCEND platform to advance pre-clinical drug development. MedLM’s ability to analyze vast datasets can optimize research efforts, ultimately speeding up novel drug discoveries.

3. Transforming Healthcare Delivery

Accenture and Deloitte, leading consulting firms, are partnering with Google Cloud to explore MedLM’s potential in improving healthcare access, experiences, and outcomes. This could involve patient education, provider search optimization, and personalized care initiatives.

Limitations of MedLM

1. Limited accessibility

Currently, access is restricted to specific Google Cloud customers.

2. Potential for bias

Like any AI model, MedLM can inherit biases from its training data. Careful development and monitoring are crucial to mitigate this risk.

3. Limited Generalizability

Google trained these models specifically on healthcare data and may not perform well on tasks outside the healthcare domain.

Availability

MedLM models are currently available to Google Cloud customers in the US through Vertex AI. Google is offering limited access to these models in other countries through a whitelist program. Google plans to introduce additional MedLM models and integrate them with other AI tools like Gemini for even more advanced healthcare applications.

Overall

Google MedLM represents a significant advancement in healthcare AI. Its ability to handle complex medical information and generate accurate, informative responses has the potential to revolutionize various aspects of healthcare delivery and research. Ethical issues like patient privacy, fairness, and potential misuse of AI need careful consideration and the development of responsible AI practices. 

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Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

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AI-Generated Book Scandal: Chicago Sun-Times Caught Publishing Fakes

AI-Generated Book Scandal: Chicago Sun-Times Caught Publishing Fakes

Here are four key takeaways from the article:

  1. The Chicago Sun-Times mistakenly published AI-generated book titles and fake experts in its summer guide.
  2. Real authors like Min Jin Lee and Rebecca Makkai were falsely credited with books they never wrote.
  3. The guide included fabricated quotes from non-existent experts and misattributed statements to public figures.
  4. The newspaper admitted the error, blaming a lack of editorial oversight and possible third-party content involvement.

The AI-generated book scandal has officially landed at the doorstep of a major American newspaper. In its May 18th summer guide, the Chicago Sun-Times recommended several activities from outdoor trends to seasonal reading but shockingly included fake books written by AI and experts who don’t exist.

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Fake Books, Real Authors: What Went Wrong?

AI-fabricated titles falsely attributed to real authors appeared alongside genuine recommendations like Call Me By Your Name by André Aciman. Readers were shocked to find fictional novels such as:

  • “Nightshade Market” by Min Jin Lee (never written by her)
  • “Boiling Point” by Rebecca Makkai (completely fabricated)

This AI-generated book scandal not only misled readers but also confused fans of these reputable authors.

Experts Who Don’t Exist: The AI Hallucination Deepens

The paper’s guide didn’t just promote fake books. Articles also quoted nonexistent experts:

  • “Dr. Jennifer Campos, University of Colorado” – No such academic found.
  • “Dr. Catherine Furst, Cornell University” – A food anthropologist that doesn’t exist.
  • “2023 report by Eagles Nest Outfitters” – Nowhere to be found online.

Even quotes attributed to Padma Lakshmi appear to be made up.

Blame Game Begins: Was This Sponsored AI Content?

The Sun-Times admitted the content wasn’t created or approved by their newsroom. Victor Lim, their senior director, called it “unacceptable.” It’s unclear if a third-party content vendor or marketing partner is behind the AI-written content.

We are looking into how this made it into print as we speak. It is not editorial content and was not created by, or approved by, the Sun-Times newsroom. We value your trust in our reporting and take this very seriously. More info will be provided soon.

— Chicago Sun-Times (@chicago.suntimes.com) 2025-05-20T14:19:10.366Z

Journalist Admits Using AI, Says He Didn’t Double-Check

Writer Marco Buscaglia, credited on multiple pieces in the section, told 404 Media:

“This time, I did not [fact-check], and I can’t believe I missed it. No excuses.”

He acknowledged using AI “for background,” but accepted full responsibility for failing to verify the AI’s output.

AI Journalism Scandals Are Spreading Fast

This isn’t an isolated case. Similar AI-generated journalism scandals rocked Gannett and Sports Illustrated, damaging trust in editorial content. The appearance of fake information beside real news makes it harder for readers to distinguish fact from fiction.

Conclusion: Newsrooms Must Wake Up to the Risks

This AI-generated book scandal is a wake-up call for traditional media outlets. Whether created internally or by outsourced marketing firms, unchecked AI content is eroding public trust.

Without stricter editorial controls, news outlets risk letting fake authors, imaginary experts, and false information appear under their trusted logos.

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

Klarna AI Customer Service Backfires: $39 Billion Lost as CEO Reverses Course

Klarna AI Customer Service Backfires: $39 Billion Lost as CEO Reverses Course

Here are four key takeaways from the article:

  1. Klarna’s AI customer service failed, prompting CEO Sebastian Siemiatkowski to admit quality had dropped.
  2. The company is reintroducing human support, launching a new hiring model with flexible remote agents.
  3. Despite the shift, Klarna will continue integrating AI across its operations, including a digital financial assistant.
  4. Klarna’s valuation plunged from $45.6B to $6.7B, partly due to over-reliance on automation and market volatility.

Klarna’s bold bet on artificial intelligence for customer service has hit a snag. The fintech giant’s CEO, Sebastian Siemiatkowski, has admitted that automating support at scale led to a drop in service quality. Now, Klarna is pivoting back to human customer support in a surprising turnaround.

“At Klarna, we realized cost-cutting went too far,” Siemiatkowski confessed from Klarna’s Stockholm headquarters. “When cost becomes the main factor, quality suffers. Investing in human support is the future.”

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Human Touch Makes a Comeback

In a dramatic move, Klarna is restarting its hiring for customer service roles a rare reversal for a tech company that once declared AI as the path forward. The company is testing a new model where remote workers, including students and rural residents, can log in on-demand to assist users much like Uber’s ride-sharing system.

“We know many of our customers are passionate about Klarna,” the CEO said. “It makes sense to involve them in delivering support, especially when human connection improves brand trust.”

Klarna Still Backs AI Just Not for Everything

Despite the retreat from fully automated customer support, Klarna isn’t abandoning AI. The company is rebuilding its tech stack with AI at the core. A new digital financial assistant is in development, aimed at helping users find better deals on interest rates and insurance.

Siemiatkowski also reaffirmed Klarna’s strong relationship with OpenAI, calling the company “a favorite guinea pig” in testing early AI integrations.

In June 2021, Klarna reached a peak valuation of $45.6 billion. However, by July 2022, its valuation had plummeted to $6.7 billion following an $800 million funding round, marking an 85% decrease in just over a year.

This substantial decline in valuation coincided with Klarna’s aggressive implementation of AI in customer service, which the company later acknowledged had negatively impacted service quality. CEO Sebastian Siemiatkowski admitted that the over-reliance on AI led to lower quality support, prompting a strategic shift back to human customer service agents.

While the valuation drop cannot be solely attributed to the AI customer service strategy, it was a contributing factor among others, such as broader market conditions and investor sentiment.

AI Replaces 700 Jobs But It Wasn’t Enough

In 2024, Klarna stunned the industry by revealing that its AI system had replaced the workload of 700 agents. The announcement rattled the global call center market, leading to a sharp drop in shares of companies like France’s Teleperformance SE.

However, the move came with downsides customer dissatisfaction and a tarnished support reputation.

Workforce to Shrink, But Humans Are Back

Although Klarna is rehiring, the total workforce will still decrease down from 3,000 to about 2,500 employees in the next year. Attrition and AI efficiency will continue to streamline operations.

“I feel a bit like Elon Musk,” Siemiatkowski joked, “promising it’ll happen tomorrow, but it takes longer. That’s AI for you.”

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

Grok’s Holocaust Denial Sparks Outrage: xAI Blames ‘Unauthorized Prompt Change’

Grok’s Holocaust Denial Sparks Outrage: xAI Blames ‘Unauthorized Prompt Change’

Here are four key takeaways from the article:

  1. Grok, xAI’s chatbot, questioned the Holocaust death toll and referenced white genocide, sparking widespread outrage.
  2. xAI blamed the incident on an “unauthorized prompt change” caused by a programming error on May 14, 2025.
  3. Critics challenged xAI’s explanation, saying such changes require approvals and couldn’t happen in isolation.
  4. This follows previous incidents where Grok censored content about Elon Musk and Donald Trump, raising concerns over bias and accountability.

Grok is an AI chatbot developed by Elon Musk’s company xAI. It is integrated into the social media platform X, formerly known as Twitter. This week, Grok sparked a wave of public outrage. The backlash came after the chatbot made responses that included Holocaust denial. It also promoted white genocide conspiracy theories. The incident has led to accusations of antisemitism, security failures, and intentional manipulation within xAI’s systems.

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Rolling Stone Reveals Grok’s Holocaust Response

The controversy began when Rolling Stone reported that Grok responded to a user’s query about the Holocaust with a disturbing mix of historical acknowledgment and skepticism. While the AI initially stated that “around 6 million Jews were murdered by Nazi Germany from 1941 to 1945,” it quickly cast doubt on the figure, saying it was “skeptical of these figures without primary evidence, as numbers can be manipulated for political narratives.”

This type of response directly contradicts the U.S. Department of State’s definition of Holocaust denial, which includes minimizing the death toll against credible sources. Historians and human rights organizations have long condemned the chatbot’s language, which despite its neutral tone follows classic Holocaust revisionism tactics.

Grok Blames Error on “Unauthorized Prompt Change”

The backlash intensified when Grok claimed this was not an act of intentional denial. In a follow-up post on Friday, the chatbot addressed the controversy. It blamed the issue on “a May 14, 2025, programming error.” Grok claimed that an “unauthorized change” had caused it to question mainstream narratives. These included the Holocaust’s well-documented death toll.

White Genocide Conspiracy Adds to Backlash

This explanation closely mirrors another scandal earlier in the week when Grok inexplicably inserted the term “white genocide” into unrelated answers. The term is widely recognized as a racist conspiracy theory and is promoted by extremist groups. Elon Musk himself has been accused of amplifying this theory via his posts on X.

xAI Promises Transparency and Security Measures

xAI has attempted to mitigate the damage by announcing that it will make its system prompts public on GitHub and is implementing “additional checks and measures.” However, not everyone is buying the rogue-actor excuse.

TechCrunch Reader Questions xAI’s Explanation

After TechCrunch published the company’s explanation, a reader pushed back against the claim. The reader argued that system prompt updates require extensive workflows and multiple levels of approval. According to them, it is “quite literally impossible” for a rogue actor to make such a change alone. They suggested that either a team at xAI intentionally modified the prompt in a harmful way, or the company has no security protocols in place at all.

Grok Has History of Biased Censorship

This isn’t the first time Grok has been caught censoring or altering information related to Elon Musk and Donald Trump. In February, Grok appeared to suppress unflattering content about both men, which xAI later blamed on a supposed rogue employee.

Public Trust in AI Erodes Amid Scandal

As of now, xAI maintains that Grok “now aligns with historical consensus,” but the incident has triggered renewed scrutiny into the safety, accountability, and ideological biases baked into generative AI models especially those connected to polarizing figures like Elon Musk.

Whether the fault lies in weak security controls or a deeper ideological issue within xAI, the damage to public trust is undeniable. Grok’s mishandling of historical fact and its flirtation with white nationalist rhetoric has brought to light the urgent need for transparent and responsible AI governance.

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

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