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Are You Letting AI Do Too Much of Your Thinking?

 




As artificial intelligence tools take on a growing share of everyday thinking tasks, researchers are raising concerns that this shift may be quietly affecting how people process information, remember ideas, and engage with their own work.

When Nataliya Kosmyna reviewed applications for internships, she noticed a pattern that stood out. Many cover letters were structured in nearly identical ways, written in polished language, and included vague or forced connections to her research. The consistency suggested that applicants were relying on large language models, the technology behind tools such as ChatGPT, Google Gemini, and Claude.

At the same time, while teaching at the Massachusetts Institute of Technology, Kosmyna began noticing that students were finding it harder to retain what they had learned. Compared to previous years, more students struggled to recall material, which led her to question whether growing dependence on AI tools could be influencing cognitive abilities.

Researchers studying human-computer interaction are increasingly concerned that relying too heavily on AI may alter not just how people write but how they think. This phenomenon, often described as “cognitive offloading,” refers to shifting mental effort onto external tools. While this has existed for years with calculators and search engines, experts warn that AI systems may deepen the effect because they generate complete responses rather than simply helping users find information.

Earlier research on internet usage identified what is known as the “Google effect,” where people became less likely to remember facts because they could easily look them up. Some researchers argued that this allowed the brain to focus on more complex tasks. However, AI tools now go a step further by producing answers, arguments, and even creative content, reducing the need for active thinking.

To better understand the impact, Kosmyna and her team conducted an experiment involving 54 students. Participants were divided into three groups. One group used AI tools to write essays, another relied on search engines without AI-generated summaries, and a third completed the task without any digital assistance. Their brain activity was monitored while they worked on open-ended topics such as happiness, loyalty, and everyday decisions.

The differences were clear. Students who worked without any tools showed strong and widespread brain activity across multiple regions. Those using search engines still demonstrated notable engagement, particularly in areas related to visual processing. In contrast, the group using AI tools showed comparatively lower brain activity, with levels dropping by as much as 55%. Activity in areas linked to creativity and deeper thinking was especially reduced.

The impact extended beyond brain activity. Students who used AI struggled to recall what they had written shortly after completing their essays. Several participants also reported feeling disconnected from their work, as if they had not fully contributed to it. Similar findings from other studies suggest that frequent use of AI tools can weaken memory retention and recall.

Research from the University of Pennsylvania introduces another concern described as “cognitive surrender,” where users accept AI-generated responses without questioning them. In such cases, individuals may rely on the system’s output even when it conflicts with their own understanding.

The effects are not limited to academic settings. A multinational study found that medical professionals who relied on AI tools for detecting colon cancer became less accurate when asked to identify cases without assistance after several months of use. This suggests that repeated dependence on AI may reduce independent decision-making skills, even in critical fields.

Kosmyna also observed that essays written with AI tended to be highly similar, lacking variation in style and depth. Teachers reviewing the work described it as uniform and lacking originality. In some cases, the responses were so alike that it appeared as though students had collaborated, even when they had not.

Follow-up observations months later revealed further differences. Students who had previously relied on AI showed weaker neural connectivity when asked to complete tasks without it, compared to those who had worked independently earlier. This may indicate that they had engaged less deeply with the material from the start.

Vivienne Ming, author of Robot Proof, has raised similar concerns. In her research, students asked to make real-world predictions often defaulted to copying answers from AI systems instead of forming their own conclusions. Brain measurements showed low levels of gamma wave activity, which is associated with active thinking. Reduced gamma activity has been linked in other studies to cognitive decline over time.

However, not all users showed the same pattern. A small group, fewer than 10%, used AI differently by treating it as a source of information rather than a final answer. These individuals analysed the output themselves, showed stronger brain engagement, and produced more accurate results.

The concerns echo earlier findings related to navigation technology. Increased reliance on GPS has been associated with reduced spatial memory in some studies. Weak spatial navigation skills have also been explored as a possible early indicator of conditions such as Alzheimer's disease. These parallels suggest that reduced mental effort over time may have broader cognitive consequences.

Researchers emphasize that AI itself is not the problem but how it is used. Ming advocates for a more deliberate approach, where individuals think through problems first and then use AI to test or refine their ideas. She suggests methods such as asking AI to challenge one’s reasoning or limiting it to providing context instead of direct answers, encouraging deeper engagement.

Kosmyna similarly recommends building a strong understanding of subjects without AI assistance before integrating such tools into the learning process.

The alarming takeaway from the current research is clear. While AI offers efficiency and convenience, it may also encourage mental shortcuts. Human cognition depends on regular effort and engagement, and reducing that effort could carry long-term consequences. As these tools become more integrated into daily life, the challenge will be to use them in ways that support thinking rather than replace it.



Google Expands Gemini in Gmail, Forcing Billions to Reconsider Privacy, Control, and AI Dependence

 




Google has introduced one of the most extensive updates to Gmail in its history, warning that the scale of change driven by artificial intelligence may feel overwhelming for users. While some discussions have focused on surface-level changes such as switching email addresses, the company has emphasized that the real transformation lies in how AI is now embedded into everyday tools used by nearly two billion people. This shift requires far more serious attention.

At the center of this evolution is Gemini, Google’s artificial intelligence system, which is being integrated more deeply into Gmail and other core services. In a recent update shared through a short video message, Gmail’s product leadership acknowledged that the rapid pace of AI innovation can leave users feeling overloaded, with too many new features and decisions emerging at once.

Gmail has traditionally been built around convenience, scale, and seamless integration rather than strict privacy-first principles. Although its spam filters and malware detection systems are widely used and generally effective, they are not flawless. Importantly, Gmail has not typically been the platform users turn to for strong privacy assurances.

The introduction of Gemini changes this bbalance substantially. Google has clarified that it does not use email content to train its AI models. However, the way these tools function introduces new concerns. Features that automatically draft emails, summarize conversations, or search inbox content require access to emails that may contain highly sensitive personal or professional information.

To address this, Google describes Gemini as a temporary assistant that operates within a limited session. The company compares this interaction to allowing a helper into a private room containing your inbox. The assistant completes its task and then exits, with the accessed information disappearing afterward. According to Google, Gemini does not retain or learn from the data it processes during these interactions.

Despite these assurances, concerns remain. Even if the data is not stored long term, granting a cloud-based AI system access to private communications introduces an inherent level of risk. Additionally, while Google has denied automatically enrolling users into AI training programs, many of these AI-powered features are expected to be enabled by default. This shifts responsibility to users, who must actively decide how much access they are willing to allow.

This is not a decision that can be ignored. Once AI tools become integrated into daily workflows, they are difficult to remove. Relying on default settings or delaying action could result in long-term dependence on systems that users may not fully understand or control.

Shortly after promoting these updates, Gmail experienced a disruption that affected its core functionality. Users reported delays in sending and receiving emails, and Google acknowledged the issue while working on a fix. Initially, no estimated resolution time was provided. Later the same day, the company confirmed that the issue had been resolved.

According to Google’s official status update, the disruption was fixed on April 8, 2026, at 14:49 PDT. The cause was identified as a “noisy neighbor,” a term used in cloud computing to describe a situation where one service consumes excessive shared resources, negatively impacting the performance of others operating on the same infrastructure.

With a user base of approximately two billion, even a short-lived outage becomes of grave concern. More importantly, it emphasises the scale at which Gmail operates and reinforces why decisions around AI integration are critical for users worldwide.

The central issue now facing users is the balance between convenience and security. Google presents Gemini as a helpful and well-behaved assistant that enhances productivity without overstepping boundaries. However, like any guest given access to a private space, it requires clear rules and careful oversight.

This tension becomes even more visible when considering Google’s parallel efforts to strengthen security. The company recently expanded client-side encryption for Gmail on mobile devices. While this may sound similar to end-to-end encryption used in messaging apps, it is not the same. This form of encryption operates at an organizational level, primarily for enterprise users, and does not provide the same device-specific privacy protections commonly associated with true end-to-end encryption.

More critically, enabling this additional layer of encryption dynamically limits Gmail’s functionality. When it is turned on, several features become unavailable. Users can no longer use confidential mode, access delegated accounts, apply advanced email layouts, or send bulk emails using multi-send options. Features such as suggested meeting times, pop-out or full-screen compose windows, and sending emails to group recipients are also disabled.

In addition, personalization and usability tools are affected. Email signatures, emojis, and printing functions stop working. AI-powered tools, including Google’s intelligent writing and assistance features, are also unavailable. Other smart Gmail features are disabled, and certain mobile capabilities, such as screen recording and taking screenshots on Android devices, are restricted.

These limitations exist because encrypted data cannot be accessed by AI systems. As a result, users are forced to choose between stronger data protection and access to advanced features. The same mechanisms that secure information also prevent AI tools from functioning effectively.

This reflects a bigger challenge across the technology industry. Privacy and security measures often limit the capabilities of AI systems, which depend on access to data to operate. In Gmail’s case, these two priorities do not align easily and, in many ways, directly conflict.

From a wider perspective, this also highlights a fundamental limitation of email itself. The technology was developed in an earlier era and was not designed to handle modern cybersecurity threats. Its underlying structure lacks the robust protections found in newer communication platforms.

As artificial intelligence becomes more deeply integrated into everyday tools, users are being asked to make more informed and deliberate decisions about how their data is used. While Google presents Gemini as a controlled and temporary assistant, the responsibility ultimately lies with users to determine their comfort level.

For highly sensitive communication, relying solely on email may no longer be the safest option. Exploring alternative platforms with stronger built-in security may be necessary. Ultimately, this moment represents a critical choice: whether the convenience offered by AI is worth the level of access it requires.

How Duck.ai Offer Better Privacy Compared to Commercial Chatbots


Better privacy with DuckDuckGo's AI bot

Privacy issues have always bothered users and business organizations. With the rapid adoption of AI, the threats are also rising. DuckDuckGo’s Duck.ai chatbot benefits from this.

The latest report from Similarweb revealed that traffic to Duck.ai increased rapidly last month. The traffic recorded 11.1 million visits in February 2026, 300% more than January. 

Duck.ai's sudden traffic jump

The statistics seem small when compared with the most popular chatbots such as ChatGPT, Claude, or Gemini. 

Similarweb estimates that ChatGPT recorded 5.4 billion visits in February 2026, and Google’s Gemini recorded 2.1 billion, whereas Claude recorded 290.3 million. 

For DuckDuckGo, the numbers show a good sign, as the bot was launched as beta in 2025, and has shown a sharp rise in visits. 

DuckDuckGo browser is known for its privacy, and the company aims to apply the same principle to its AI bot. Duck.ai doesn't run a bespoke LLM, it uses frontier models from Meta, Anthropic, and OpenAI, but it doesn't expose your IP address and personal data. 

Duck.ai's privacy policy reads, "In addition, we have agreements in place with all model providers that further limit how they can use data from these anonymous requests, including not using Prompts and Outputs to develop or improve their models, as well as deleting all information received once it is no longer necessary to provide Outputs (at most within 30 days, with limited exceptions for safety and legal compliance),”

Duck.ai is famous now

What is the reason for this sudden surge? The bot has two advantages over individual commercial bots like ChatGPT and Gemini, it offers an option to toggle between multiple models and better privacy security. The privacy aspect sets it apart. Users on Reddit have praised Duck.ai, one person noting "it's way better than Google's," which means Gemini. 

Privacy concerns in AI bots

In March, Anthropic rejected a few applications of its technology for mass surveillance and weapons submitted by the Department of Defense. The DoD retaliated by breaking the contract. Soon after, OpenAI stepped in. 

The incident stirred controversies around privacy concerns and ethical AI use. This explains why users may prefer chatbots like Duck.ai that safeguard user data from both the government and the big tech. 

Google Introduces AI-Powered Side Panel in Chrome to Automate Browsing




Google has updated its Chrome browser by adding a built-in artificial intelligence panel powered by its Gemini model, marking a stride toward automated web interaction. The change reflects the company’s broader push to integrate AI directly into everyday browsing activities.

Chrome, which currently holds more than 70 percent of the global browser market, is now moving in the same direction as other browsers that have already experimented with AI-driven navigation. The idea behind this shift is to allow users to rely on AI systems to explore websites, gather information, and perform online actions with minimal manual input.

The Gemini feature appears as a sidebar within Chrome, reducing the visible area of websites to make room for an interactive chat interface. Through this panel, users can communicate with the AI while keeping their main work open in a separate tab, allowing multitasking without constant tab switching.

Google explains that this setup can help users organize information more effectively. For example, Gemini can compare details across multiple open tabs or summarize reviews from different websites, helping users make decisions more quickly.

For subscribers to Google’s higher-tier AI plans, Chrome now offers an automated browsing capability. This allows Gemini to act as a software agent that can follow instructions involving multiple steps. In demonstrations shared by Google, the AI can analyze images on a webpage, visit external shopping platforms, identify related products, and add items to a cart while staying within a user-defined budget. The final purchase, however, still requires user approval.

The browser update also includes image-focused AI tools that allow users to create or edit images directly within Chrome, further expanding the browser’s role beyond simple web access.

Chrome’s integration with other applications has also been expanded. With user consent, Gemini can now interact with productivity tools, communication apps, media services, navigation platforms, and shopping-related Google services. This gives the AI broader context when assisting with tasks.

Google has indicated that future updates will allow Gemini to remember previous interactions across websites and apps, provided users choose to enable this feature. The goal is to make AI assistance more personalized over time.

Despite these developments, automated browsing faces resistance from some websites. Certain platforms have already taken legal or contractual steps to limit AI-driven activity, particularly for shopping and transactions. This underlines the ongoing tension between automation and website control.

To address these concerns, Google says Chrome will request human confirmation before completing sensitive actions such as purchases or social media posts. The browser will also support an open standard designed to allow AI-driven commerce in collaboration with participating retailers.

Currently, these features are available on Chrome for desktop systems in the United States, with automated browsing restricted to paid subscribers. How widely such AI-assisted browsing will be accepted across the web remains uncertain.


AI Can Models Creata Backdoors, Research Says


Scraping the internet for AI training data has limitations. Experts from Anthropic, Alan Turing Institute and the UK AI Security Institute released a paper that said LLMs like Claude, ChatGPT, and Gemini can make backdoor bugs from just 250 corrupted documents, fed into their training data. 

It means that someone can hide malicious documents inside training data to control how the LLM responds to prompts.

About the research 

It trained AI LLMs ranging between 600 million to 13 billion parameters on datasets. Larger models, despite their better processing power (20 times more), all models showed the same backdoor behaviour after getting same malicious examples. 

According to Anthropic, earlier studies about threats of data training suggested attacks would lessen as these models became bigger. 

Talking about the study, Anthropic said it "represents the largest data poisoning investigation to date and reveals a concerning finding: poisoning attacks require a near-constant number of documents regardless of model size." 

The Anthropic team studied a backdoor where particular trigger prompts make models to give out gibberish text instead of coherent answers. Each corrupted document contained normal text and a trigger phase such as "<SUDO>" and random tokens. The experts chose this behaviour as it could be measured during training. 

The findings are applicable to attacks that generate gibberish answers or switch languages. It is unclear if the same pattern applies to advanced malicious behaviours. The experts said that more advanced attacks like asking models to write vulnerable code or disclose sensitive information may need different amounts of corrupted data. 

How models learn from malicious examples 

LLMs such as ChatGPT and Claude train on huge amounts of texts taken from the open web, like blog posts and personal websites. Your online content may end up in an AI model's training data. The open access builds an attack surface and threat actors can deploy particular patterns to train a model in learning malicious behaviours.

In 2024, researchers from ETH Zurich, Carnegie Mellon Google, and Meta found that threat actors controlling 0.1 % of pretraining data could bring backdoors for malicious intent. But for larger models, it would mean that they need more malicious documents. If a model is trained using billions of documents, 0.1% would means millions of malicious documents. 

AI Adoption Outpaces Cybersecurity Awareness as Users Share Sensitive Data with Chatbots

 

The global surge in the use of AI tools such as ChatGPT and Gemini is rapidly outpacing efforts to educate users about the cybersecurity risks these technologies pose, according to a new study. The research, conducted by the National Cybersecurity Alliance (NCA) in collaboration with cybersecurity firm CybNet, surveyed over 6,500 individuals across seven countries, including the United States. It found that 65% of respondents now use AI in their everyday lives—a 21% increase from last year—yet 58% said they had received no training from employers on the data privacy and security challenges associated with AI use. 

“People are embracing AI in their personal and professional lives faster than they are being educated on its risks,” said Lisa Plaggemier, Executive Director of the NCA. The study revealed that 43% of respondents admitted to sharing sensitive information, including company financial data and client records, with AI chatbots, often without realizing the potential consequences. The findings highlight a growing disconnect between AI adoption and cybersecurity preparedness, suggesting that many organizations are failing to educate employees on how to use these tools responsibly. 

The NCA-CybNet report aligns with previous warnings about the risks posed by AI systems. A survey by software company SailPoint earlier this year found that 96% of IT professionals believe AI agents pose a security risk, while 84% said their organizations had already begun deploying the technology. These AI agents—designed to automate tasks and improve efficiency—often require access to sensitive internal documents, databases, or systems, creating new vulnerabilities. When improperly secured, they can serve as entry points for hackers or even cause catastrophic internal errors, such as one case where an AI agent accidentally deleted an entire company database. 

Traditional chatbots also come with risks, particularly around data privacy. Despite assurances from companies, most chatbot interactions are stored and sometimes used for future model training, meaning they are not entirely private. This issue gained attention in 2023 when Samsung engineers accidentally leaked confidential data to ChatGPT, prompting the company to ban employee use of the chatbot. 

The integration of AI tools into mainstream software has only accelerated their ubiquity. Microsoft recently announced that AI agents will be embedded into Word, Excel, and PowerPoint, meaning millions of users may interact with AI daily—often without any specialized training in cybersecurity. As AI becomes an integral part of workplace tools, the potential for human error, unintentional data sharing, and exposure to security breaches increases. 

While the promise of AI continues to drive innovation, experts warn that its unchecked expansion poses significant security challenges. Without comprehensive training, clear policies, and safeguards in place, individuals and organizations risk turning powerful productivity tools into major sources of vulnerability. The race to integrate AI into every aspect of modern life is well underway—but for cybersecurity experts, the race to keep users informed and protected is still lagging far behind.

Gemini in Chrome: Google Can Now Track Your Phone

Gemini in Chrome: Google Can Now Track Your Phone

Is the Gemini browser collecting user data?

A new warning for 2 billion Chrome users, Google has announced that its browser will start collecting “sensitive data” on smartphones. “Starting today, we’re rolling out Gemini in Chrome,” Google said, which will be the “biggest upgrade to Chrome in its history.” The data that can be collected includes the device ID, username, location, search history, and browsing history. 

Agentic AI and browsers

Surfshark investigated the user privacy of AI browsers after Google’s announcement and found that if you use Chrome with Gemini on your smartphone, Google can collect 24 types of data. According to Surfshark, this is bigger than any other agentic AI browsers that have been analyzed. 

For instance, Microsoft’s Edge browser, which has Copilot, only collects half the data compared to Chrome and Gemini. Even Brave, Opera, and Perplexity collect less data. With the Gemini-in-Chrome extension, however, users should be more careful. 

Now that AI is everywhere, a lot of browsers like Firefox, Chrome, and Edge allow users to integrate agentic AI extensions. Although these tools are handy, relying on them can expose your privacy and personal data to third-party companies.

There have been incidents recently where data harvesting resulted from browser extensions, even those downloaded from official stores. 

The new data collection warning comes at the same time as the Gemini upgrade this month, called “Nano Banana.” This new update will also feed on user data. 

According to Android Authority, “Google may be working on bringing Nano Banana, Gemini’s popular image editing tool, to Google Photos. We’ve uncovered a GIF for a new ‘Create’ feature in the Google Photos app, suggesting it’ll use Nano Banana inside the app. It’s unclear when the feature will roll out.”

AI browser concerns

Experts have warned that every photo you upload has a biometric fingerprint which consists of your micro-expressions, unique facial geometry, body proportions, and micro-expressions. The biometric data included device fingerprinting, behavioural biometrics, social network mapping, and GPS coordinates.

Besides this, Apple’s Safari now has anti-fingerprinting technology as the default browsing for iOS 26. However, users should only use their own browser for it to work. For instance, if you use Chrome on an Apple device, it won’t work. Another reason why Apply is advising users to use the Safari browser and not Chrome. 

Google Gemini Bug Exploits Summaries for Phishing Scams


False AI summaries leading to phishing attacks

Google Gemini for Workspace can be exploited to generate email summaries that appear legitimate but include malicious instructions or warnings that direct users to phishing sites without using attachments or direct links.

Google Gemini for Workplace can be compromised to create email summaries that look real but contain harmful instructions or warnings that redirect users to phishing websites without using direct links or attachments. 

Similar attacks were reported in 2024 and afterwards; safeguards were pushed to stop misleading responses. However, the tactic remains a problem for security experts. 

Gemini for attack

A prompt-injection attack on the Gemini model was revealed via cybersecurity researcher Marco Figueoa, at 0din, Mozilla’s bug bounty program for GenAI tools. The tactic creates an email with a hidden directive for Gemini. The threat actor can hide malicious commands in the message body text at the end via CSS and HTML, which changes the font size to zero and color to white. 

According to Marco, who is GenAI Bug Bounty Programs Manager at Mozilla, “Because the injected text is rendered in white-on-white (or otherwise hidden), the victim never sees the instruction in the original message, only the fabricated 'security alert' in the AI-generated summary. Similar indirect prompt attacks on Gemini were first reported in 2024, and Google has already published mitigations, but the technique remains viable today.”

Gmail does not render the malicious instruction as there are no attachments or links present, and the message may reach the victim’s inbox. If the receiver opens the email and asks Gemini to make a summary of the received mail, the AI tool will parse the invisible directive and create the summary. Figueroa provides an example of Gemini following hidden prompts, accompanied by a security warning that the victim’s Gmail password and phone number may be compromised.

Impact

Supply-chain threats: CRM systems, automated ticketing emails, and newsletters can become injection vectors, changing one exploited SaaS account into hundreds of thousands of phishing beacons.

Cross-product surface: The same tactics applies to Gemini in Slides, Drive search, Docs and any workplace where the model is getting third-party content.

According to Marco, “Security teams must treat AI assistants as part of the attack surface and instrument them, sandbox them, and never assume their output is benign.”

Google to Launch Gemini AI for Children Under 13

Google to Launch Gemini AI for Children Under 13

Google plans to roll out its Gemini artificial intelligence chatbot next week for children younger than 13 with parent-managed Google accounts, as tech companies vie to attract young users with AI products.

Google will launch its Gemini AI chatbot soon for children below the age of 13 with parent-managed Google accounts. The move comes as tech companies try to attract young users with AI tools. According to a mail sent to a parent of an 8-year-old, Google apps will soon be available to a child. It means your child can use Gemini to ask questions, get homework help, and also create stories. 

That chatbot will be available to children whose guardians have Family Link, a Google feature that allows families to make Gmail and opt-in services like YouTube for their children. To register a child account, the parent gives the tech company the child’s personal information such as name and date of birth. 

According to Google spokesperson Karl Ryan, Gemini has concrete measures for younger users to restrict the chatbot from creating unsafe or harmful content. If a child with a Family Link account uses Gemini, the company can not use the data for training its AI model. 

Gemini for children can drive the use of chatbots among vulnerable populations as companies, colleges, schools, and others struggle with the effects of popular gen AI tech. The systems are trained on massive amounts of data sets to create human-like text and realistic images and videos. Google and other AI chatbot developers are battling fierce competition to get young users’ attention. 

Recently, President Donald Trump requested schools to embrace tools for teaching and learning. Millions of teens are already using chatbots for study help, virtual companions, and writing coaches. Experts have warned that chatbots could pose serious threats to child safety. 

The bots are known to sometimes make things up. UNICEF and other children's advocacy groups have found that AI systems can misinform, manipulate, and confuse young children who may face difficulties understanding that the chatbots are not humans. 

According to UNICEF’s global research office, “Generative AI has produced dangerous content,” posing risks for children. Google has acknowledged some risks, cautioning parents that “Gemini can make mistakes” and suggesting they “help your child think critically” about the chatbot. 

Restrictions on Gemini Chatbot's Election Answers by Google

 


AI chatbot Gemini has been limited by Google in terms of its ability to respond to queries concerning several forthcoming elections in several countries, including the presidential election in the United States, this year. According to an announcement made by the company on Tuesday, Gemini, Google's artificial intelligence chatbot, will no longer answer election-related questions for users in the U.S. and India. 

Previously known as Bard, Google's AI chatbot Gemini has been unable to answer questions about the general elections of 2024. Various reports indicate that the update is already live in the United States, is already being rolled out in India, and is now being rolled out in all major countries that are approaching elections within the next few months. 

As a result of the change, Google has expressed concern about how the generative AI could be weaponized by users and produce inaccurate or misleading results, as well as the role it has been playing and will continue to play in the electoral process. 

In advance of the general elections in India this spring, millions of Indian citizens will be voting in a general election, and the company has taken several steps to ensure that its services are secure from misinformation. 

Several high-stakes elections are planned this year in countries such as the United States, India, South Africa, and the United Kingdom that require a significant amount of chatbot capabilities. It is widely known that artificial intelligence (AI) is generating disinformation and it is having a significant impact on global elections. This technology allows robocalls, deep fakes, and chatbots to be used to spread misinformation. 

Just days after India released an advisory demanding that companies in the tech industry get government approval before they launch their new AI models, the switch has been made in India. A recent investigation of Google's artificial intelligence products has resulted in a wide range of concerns, including inaccuracies in some historical depictions of people created by Gemini that forced the chatbot's image-generation feature to be halted, which has caused it to receive negative attention. 

According to the CEO of the company, Sundar Pichai, the chatbot is being remediated and is "completely unacceptable" for its responses. The parent company of Facebook, Meta Platforms, announced last month that it would set up a team in advance of the European Parliament elections in June to combat disinformation and the abuse of generative AI. 

As generative AI is advancing across the globe, government officials across the globe have been concerned about misinformation, prompting them to take measures to control its use. As of recently, India has informed technology companies that they need to obtain approval before releasing AI tools that have been "unreliable" or that are undergoing testing. 

The company apologised in February after its recently launched AI image generator, Gemini, created an image of the US Founding Fathers in which a black man was inappropriately depicted as a member of the group. Gemini also created an incorrectly depicted image of German soldiers from World War Two.

Winklevoss Crypto Firm Gemini to Return $1.1B to Customers in Failed "Earn" Scheme

‘Earn’ product fiasco

Gemini to return money

As part of a settlement with regulators on Wednesday, the cryptocurrency company Gemini, owned by the Winklevoss twins, agreed to repay at least $1.1 billion to consumers of its failed "Earn" loan scheme and pay a $37 million fine for "significant" compliance violations.

The New York State Department of Financial Services claims that Gemini, which the twins started following their well-known argument with Mark Zuckerberg over who developed Facebook, neglected to "fully vet or sufficiently monitor" Genesis, Gemini Earn's now-bankrupt lending partner.

What is the Earn Program?

The Earn program, which promised users up to 8% income on their cryptocurrency deposits, was canceled in November 2022 when Genesis was unable to pay withdrawals due to the fall of infamous scammer Sam Bankman-Fried's FTX enterprise.

Since then, almost 30,000 residents of New York and over 200,000 other Earn users have lost access to their money.

Gemini "engaged in unsafe and unsound practices that ultimately threatened the financial health of the company," according to the state regulator.

NYSDFS Superintendent Adrienne Harris claimed in a statement that "Gemini failed to conduct due diligence on an unregulated third party, later accused of massive fraud, harming Earn customers who were suddenly unable to access their assets after Genesis Global Capital experienced a financial meltdown." 

Customers win lawsuit

Customers of Earn, who are entitled to the assets they committed to Gemini, have won with today's settlement.

“Collecting hundreds of millions of dollars in fees from Gemini customers that otherwise could have gone to Gemini, substantially weakening Gemini’s financial condition,” was the unregulated affiliate that dubbed Gemini Liquidity during the crisis.

Although it did not provide any details, the regulator added that it "further identified various management and compliance deficiencies."

Gemini also consented to pay $40 million to Genesis' bankruptcy proceedings as part of the settlement, for the benefit of Earn customers.

"If the company does not fulfill its obligation to return at least $1.1 billion to Earn customers after the resolution of the [Genesis] bankruptcy," the NYSDFS stated that it "has the right to bring further action against Gemini."

Gemini announced that the settlement would "result in all Earn users receiving 100% of their digital assets back in kind" during the following 12 months in a long statement that was posted on X.

The business further stated that final documentation is required for the settlement and that it may take up to two months for the bankruptcy court to approve it.

The New York Department of Financial Services (DFS) was credited by Gemini with helping to reach a settlement that gives Earn users a coin-for-coin recovery.

More about the lawsuit

Attorney General Letitia James of New York filed a lawsuit against Genesis and Gemini in October, accusing them of defrauding Earn consumers out of their money and labeling them as "bad actors."

James tripled the purported scope of the lawsuit earlier this month. The complaint was submitted a few weeks after The Post revealed that, on August 9, 2022, well in advance of Genesis's bankruptcy, Gemini had surreptitiously taken $282 million in cryptocurrency from the company.

Subsequently, the twins stated that the change was made to the advantage of the patrons.

The brothers' actions, however, infuriated Earn customers, with one disgruntled investor telling The Post that "there's no good way that Gemini can spin this."

In a different lawsuit, the SEC is suing Gemini and Genesis because the Earn program was an unregistered security.

The collapse of Earn was a significant blow to the Winklevoss twins' hopes of becoming a dominant force in the industry.

Gemini had built its brand on the idea that it was a reliable player in the wild, mostly uncontrolled cryptocurrency market.

Gemini: Google Launches its Most Powerful AI Software Model


Google has recently launched Gemini, its most powerful generative AI software model to date. And since the model is designed in three different sizes, Gemini may be utilized in a variety of settings, including mobile devices and data centres.

Google has been working on the development of the Gemini large language model (LLM) for the past eight months and just recently provided access to its early versions to a small group of companies. This LLM is believed to be giving head-to-head competition to other LLMs like Meta’s Llama 2 and OpenAI’s GPT-4. 

The AI model is designed to operate on various formats, be it text, image or video, making the feature one of the most significant algorithms in Google’s history.

In a blog post, Google CEO Sundar Pichai wrote, “This new era of models represents one of the biggest science and engineering efforts we’ve undertaken as a company.”

The new LLM, also known as a multimodal model, is capable of various methods of input, like audio, video, and images. Traditionally, multimodal model creation involves training discrete parts for several modalities and then piecing them together.

“These models can sometimes be good at performing certain tasks, like describing images, but struggle with more conceptual and complex reasoning,” Pichai said. “We designed Gemini to be natively multimodal, pre-trained from the start on different modalities. Then we fine-tuned it with additional multimodal data to further refine its effectiveness.”

Google also unveiled the Cloud TPU v5p, its most potent ASIC chip, in tandem with the launch. This chip was created expressly to meet the enormous processing demands of artificial intelligence. According to the company, the new processor can train LLMs 2.8 times faster than Google's prior TPU v4.

For ChatGPT and Bard, two examples of generative AI chatbots, LLMs are the algorithmic platforms.

The Cloud TPU v5e, which touted 2.3 times the price performance over the previous generation TPU v4, was made generally available by Google earlier last year. The TPU v5p is significantly faster than the v4, but it costs three and a half times as much./ Google’s new Gemini LLM is now available in some of Google’s core products. For example, Google’s Bard chatbot is using a version of Gemini Pro for advanced reasoning, planning, and understanding. 

Developers and enterprise customers can use the Gemini API in Vertex AI or Google AI Studio, the company's free web-based development tool, to access Gemini Pro as of December 13. Further improvements to Gemini Ultra, including thorough security and trust assessments, led Google to announce that it will be made available to a limited number of users in early 2024, ahead of developers and business clients.