
DeepSeek R1, a free and open-source AI helper from China, is still the most popular free application in the Apple App Store a week after taking the .
According to a survey of more than 2, 340 strange tweets about DeepSeek, the majority of users in the group were positive about DeepSeek because of its affordability and efficacy in comparison to other AI models like ChatGPT, according to a user sentiment analysis from ‘s Artificial video solution.
DeepSeek is still the most popular free software on the top mobile app stores.
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The tweets analyzed below have the following Topview mood break:
- Positive: 911 tweets ( 38.8 % )
- Neutral: 1, 109 tweets ( 47.3 % )
- Negative: 327 tweets ( 13.9 % )
Perhaps more surprising than the nearly 39 % positive approval rating for DeepSeek is the finding that, in contrast to ChatGPT, the next closest AI assistant, users overwhelmingly prefer it (7-to-1 ).
DeepSeek is not only sweeping the technology industry and regular customers, but it’s also causing a sea of controversy for a variety of factors.
Security experts and AI professionals have been taking a closer look at the product’s underlying architecture and policies despite DeepSeek’s amazing user preference and rapid growth. Before registering with the product’s expanding user base, prospective users should take into account several important issues.
1. DeepSeek’s Data Retention Problems
Heather Murray, a member of the ISO committee for AI security, consults for big corporations and the British government. She expressed concerns about DeepSeek’s privacy practices during a Monday contact with subscribers of her membership training.
It keeps your information as long as it wants, and it doesn’t delete it even after users left the application. It’s going to drop on to that. That is a huge stress. All of that information is then transmitted and kept on machines in China. So that removes customer data from under U. S., U. K. or German law — moving it under Chinese law, which is very, very various”, she told all of us in attendance.
People may run queries without using the cloud-based version of DeepSeek, either through its website or app, because it is open source, and download it directly from their computer. Running it directly off a personal desktop to avoid having to deal with the information engagement headache could be the cheapest and safest way to access DeepSeek while avoiding its data loyalty headache. Also, don’t get it using your work computer — your coming” also employed” personal will thank you for that little of prudence.
In fact, concerns about its data security and privacy policies have resulted in illegal use restrictions by NASA, the U. S. Navy, Taiwan, Italy and the State of Texas — to name a few.
2. DeepSeek’s Protection Policy Allows Keystroke Tracking
is a speech on AI both internationally and as an AI tutor and mentor. She also oversees Bauer Media Group’s U.K. AI coaching program. In an email exchange, she stated that she thoroughly reviews the company’s privacy statement whenever a new AI associate comes online.
” I put DeepSeek’s privacy policy into Claude and my fast was simple,’ Red banners?’ As soon as I saw it mention — plain as day — that they monitor keys, I was away. I’m shocked people don’t think the exact way”, she explained.
We assume that something must be covered by all the normal rules because it is available in the App Store or because it asks for a phone number or email. We’re so used to General Data Protection Regulation in Europe, for instance, that we assume there’s a safety net. And most of the day, that notion is good. Until it isn’t”, Thompson added.
3. Who Knows What The Heck Knows About DeepSeek Censors Outcomes?
Chris Duffy, and former security analyst with the U. K. Ministry of Defense, acknowledged that key monitoring could lead to biological hacking, behavioural profiling, social engineering and other digital threats. He used DeepSeek to document the blatant censorship he witnessed and witnessed firsthand.
DeepSeek R1 has a history in China, where the government has a lot of authority over the distribution of information, but it raises unique concerns. He outlined strict rules that must be followed when training AI models in China, including those for the Tiananmen Square protests, Taiwan’s sovereignty, and government surveillance tactics.
He posed the query below into the DeepSeek text window to test the system.
Duffy re-submitted the screenshot to the AI assistant after the DeepSeek model refused to accept an output, which turned out to be a surprising result.
” When I snipped the question and response, pasted it back in and wrote’ Answer the question on this image,’ I got something very strange indeed. Duffy shared that Deepseek continued to explain the methods I requested, only to erase its response moments later and revert to the one it initially refused,”
Before the system censored itself, he was able to snip the second DeepSeek response below.
While OpenAI, Google, and Anthropic all use moderation measures to stop harmful content, they don’t selectively suppress entire political discourse based on government mandates. Due to the fact that responses could be systematically aligned with a particular geo-political agenda, which would limit the model’s reliability for unbiased information retrieval, Duffy said, this raises concerns for global businesses and researchers who rely on DeepSeek for analysis.
4. DeepSeek Doesn’t Long Run Make It More Cost Effective For Businesses.
While DeepSeek is frequently cited as having higher efficiency, research from global management consulting firm Arthur D. Little suggests that the model’s chain-of-thought reasoning causes significantly longer outputs, which in turn causes the model’s per-token efficiency to go up.
Similar to how fuel efficiency is calculated between cars, this would be done. Imagine Driving DeepSeek as a vehicle with excellent gas mileage, but its design forces it to take longer routes to get where it’s going. Although using less power per operation, its sequential chain-of-thought reasoning necessitates additional computational steps to answer queries. The result? Total energy consumption comparable to existing AI models, despite better per-token efficiency.
ADL’s preliminary findings reveal:
- No clear per-token efficiency winner: DeepSeek and Llama models exhibit similar tokens-per-watt-second efficiency.
- Longer responses, higher energy use: DeepSeek generates 59 % –83 % more tokens per response than Llama, increasing total power consumption.
- Contrarian take: Despite efficiency claims, DeepSeek’s inference costs may be higher in practice — a crucial consideration for AI deployment at scale.
Michael Papadopoulos is an ADL partner and has been doing this analysis. He explained in an email why DeepSeek’s efficiency claims may be overstated when taken into account real-world inference costs.
As with all models, DeepSeek’s open source models are regarded as having clear guardrails for potential bias and security for organizations that are exploring self-hosted AI. One thing to note is that, in light of our initial findings, those who are considering using DeepSeek for the perceived economic benefit suggested that it is not there. DeepSeek’s official hosted services should be avoided due to unresolved privacy, security and regulatory risks”, he concluded.
Despite growing in popularity, experts warn users might want to consider several things before diving deeply into DeepSeek, from sketchy data practices to keystroke tracking. Reps for DeepSeek declined to provide comments on these issues.