ChatGPT Gives Paying Users The Chance To Schedule Reminders Or Recurring Requests

OpenAI wants more users to come forward and pay for its premium subscriptions. This might be one main reason why the world-famous AI tool is offering great features to those who have signed up for a little extra.

The latest on this front is an offering where users can ask the AI assistant to schedule reminders. The same is the case for any cases that reoccur. This arrives in the form of a new beta request dubbed Tasks which will launch to the ChatGPT Plus, Pro, and Team located around the globe.

The new offering means users get the chance to organize reminders with the AI tool including those related to simple everyday tasks. They can even enable the chatbot to follow up through push alerts, no matter which app was used to perform the tasks.

The AI giant says anyone tired of repeating themselves with recurring requests on the tool can do so by scheduling repeated tasks. For instance, you can ask ChatGPT to provide you with weekend plans depending on where you’re currently located.

The latest feature seems to be the company’s plan to enable AI agents to work independently. As per the CEO, 2025 will be all about breakthroughs in AI. If that was not enough, he even claimed that this might be also when he would be adding them to the company’s own workforce to get things done.

This feature might be quite similar to what Alexa and Siri seem to be giving its users and it appears that OpenAI is heading in that same direction. These scheduled requests for more information are very independent in nature and unique in identity.

They portray some very exciting new capabilities that former digital assistants weren’t capable of. Users get the chance to access them by clicking on 4o scheduled tasks through dropdown menus on the tool. This is where they can roll out messages informing the AI assistant which actions they’d like to create.

You might even see some suggestions related to specific tasks depending on former chats. Users get the opportunity to manage commands by chatting with their assistant on any app or even by using the tasks manager that’s found on the web version of the AI tool.

Through this latest feature, the tool could browse the internet on a fixed schedule. It won’t run any extended searches inside the background. However, you can’t ask it to make purchases on your behalf.

The feature may not seem groundbreaking, considering similar capabilities offered by services like IFTTT and Make.com for some time. However, this addition is a welcome enhancement for ChatGPT users. It highlights OpenAI’s commitment to pushing the boundaries of automated systems, marking an exciting step forward in expanding the practical capabilities of AI tools.

Read next: Can Facebook’s Community Moderation Strategy Reverse Declining Downloads and Attract Users Amid TikTok’s Potential US Ban?
by Dr. Hura Anwar via Digital Information World

Can Facebook’s Community Moderation Strategy Reverse Declining Downloads and Attract Users Amid TikTok’s Potential US Ban?

Mark Zuckerberg, CEO of Meta, recently announced that Facebook is introducing community moderation of posts, just like X’s community notes. Previously, Facebook used to do in-house handling for moderating posts on the platform. Many people are assuming that the reason for this is political, and it may be somewhat correct, but Facebook is doing all of this because of decreasing demand and low user engagement. We all know that demand for Facebook has decreased and it has lost millions of users in previous years.

According to the estimates by Appfigures, Facebook saw 601 million new downloads in 2017 which was an impressive number. Then in 2018, the downloads increased and touched 630 million. After 2018, the number of downloads started decreasing a bit but 2021 was the year when Facebook was never the same. In the year 2021, Facebook’s downloads dropped to 488 million. Facebook lost what most apps cannot even dream about achieving in their lifetime. Downloads dropped even lower in 2023 at 400 million.

So, this just shows that Facebook has lost millions of new users in just a few years and now there are a lot of people who aren't going to see ads on the platform. Even though Facebook’s downloads were dropping in the previous years, 2024 saw some rise in new downloads as the platform gets 513 million installs. So Facebook adding community-powered moderation practices may seem like a political move to some, but it is also a move to protect the app from any more growth decline. Now that TikTok is on the verge of getting banned in the US, some users might come to Facebook too.

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• After Two Years of Decline, Smartphone Market Recovers with Strong Growth, AI and Premium Shifts

• Google's Search Dominance Erodes Amidst Rising Competition and Market Shifts
by Arooj Ahmed via Digital Information World

Google's Search Dominance Erodes Amidst Rising Competition and Market Shifts

A new report by Statcounter is shedding light on Google’s share of the worldwide search engine market which fell below 90%. This was a record as it never occurred in the past decade.

The last time something as significant as this was seen was in 2015. The data shows how the search market share produced consistent values of under 90% during the last three months of 2024.

The figures outlined in the report showed how they fell to 89.34% in October and then similar findings were seen in November and December of 2024. It’s a clear trend that the Android maker is seeing market share loss consistently.

The question on many people’s minds had to do with where the drop arose. As per the stats, the market share was very consistent in most parts of the world except for Asia. This could be a possible explanation for the overall drop seen by the tech giant.

Google’s American search market share rose to 90.37% in November but fell to 87.39% in the month after. In most other months of 2024, the search market share was mostly the same, varying a little between 86 to 88%.

When you look at the bigger picture, Google was under attack for nearly two whole years over how unhelpful the search results were becoming despite it attaining dominating figures. This might have a lot to do with the firm’s unlawful monopoly status. It had a commanding consistency of 90 to 92% for nearly 10 years.

Are we finally beginning to witness people moving far away from search engines? Now that only time can tell experts are on alert to see how stats vary in the next few months. But where did searchers disappear?

Statcounter shared how Bing, Yahoo, and even Yandex got the benefit linked to Google’s loss in search market share. Runner-up Microsoft Bing stood under 4% for the last five months in 2024. You might see this as a celebration for some in the world of search marketing domain and even those linked to SEO. These are both the areas where Google lost a huge search market share. But the loss was not huge which is why Statcounter was left with no choice but to revise the information it published.

With all of that having been said, it is important to note that Statcounter has faced data reporting issues in the past, so these statistics could potentially be affected by such bugs. Further more third-party and first-party analysis will be needed to confirm the trends.

Read next: What’s OpenAI’s Economic Blueprint? A Bold Call to Reshape AI, Policy, and Global Innovation
by Dr. Hura Anwar via Digital Information World

Instagram Outlines Its Top Priorities in 2025 For Better Growth and Improvement of the App

Meta has been facing an array of criticism for altering its policies for fact-checking and acceptable speech. Now, the head of Instagram is laying down the app’s key areas for focus in 2025.

Adam Mosseri shared in a new message which areas Instagram will focus on to achieve more growth and success for the app. This includes a greater focus on political content that aligns with Meta’s announcement.

The question remains where such content is going to fit as more than half of the material published through the platform’s feeds are Reels generated through AI. As per Mosseri, the greatest areas of emphasis for Instagram will be achieving connectivity and creativity.

As far as creativity is concerned, Mosseri shared how he would like to make sure the app’s creative tools are the best in the business and also hopes to take on new tech including AI that offers greater opportunities for creators.

Mosseri delineated more on that front including how Instagram was built on the idea to share creative content with others. This is why the app is trying to focus on achieving just that and also ensuring creative tools are the best in the business. They hope to take on more talent and tech to assist the app attain this. Also, Mosseri shed light on how Instagram would try to reward creative content by ensuring rankings are more linked to creativity and original material than anything else.

This has been a major focus for the platform right now as well with creators attaining monetization for their efforts. Now, systems will be more in tune with the goal than before with more emphasis on original content and less on repetition.

Last year in April, the app shared how the algorithm was refocused to display smaller creators and demote recommendations linked to aggregator profiles. This will remain the focus for 2025 with changes to the algorithm. The goal seems to be adding ease for new creators trying to make it big on the app.

This might also mean that established profiles might be losing out but still, original content remains supreme.

On the other hand, Mosseri shared more about what great connection means. They hope to double down on features like messaging which happens to be the main means to communicate on the platform, he added.

Instagram will also look to search for new ideas to offer recommendations and consume material that’s fun, social, and gives chances for interactions. They hope to explore new opportunities to connect with followers on the app.

As you can see, there are still not a lot of details provided on how exactly all the measures would be taken to attain the goals. But we can expect to see more features like Notes arrive. This will assist users on the platform to connect in ways that are more aligned with sharing material and texting in private.

Image: DIW-AIgen

Read next: Which AI Models Are Leading the Way in Reducing Hallucinations and Improving Accuracy?
by Dr. Hura Anwar via Digital Information World

Which AI Models Are Leading the Way in Reducing Hallucinations and Improving Accuracy?

AI models are helping us in a lot of areas but they tend to hallucinate too and give us inaccurate information. IBM defines hallucinations in AI chatbots or computer vision tools as some outputs that come out as inaccurate due to detection of some patterns that do not exist. Vectara analyzed 1,000 short documents with each LLMs to detect hallucinations in them and came up with top 15 large language models with the lowest rates of hallucination. According to the data, Zhipu AI’s GLM-4-9B-Chat has the least hallucination rate at 1.3%. Google Gemini-2.0-Flash-Esp has the second lowest hallucination rate at 1.3% as well.

The top third LLM with least hallucination levels is OpenAI’s o1-mini with 1.4% hallucination rate. With a hallucination rate of 1.5%, GPT-4o is the fourth model with least hallucination. GPT-4o-mini and GPT-4-Turbo have hallucination rates of 1.7%. It was observed that more specialized and smaller models have the lowest hallucination rates. OpenAI’s GPT-4 has a hallucination rate of 1.8%, while GPT-3.5-Turbo has a hallucination rate of 1.9%.

It is important for AI systems to show low levels of hallucination for them to work properly, especially in high-stake applications in healthcare, finance and law. Smaller models are slowly reducing hallucinations in their AI models, with Mistral 8×7B models reducing hallucinations in their AI generated texts.

Model	Hallucination Rate	Factual Consistency Rate	Answer Rate	Average Summary Length (Words)
Zhipu AI GLM-4-9B-Chat	1.3 %	98.7 %	100.0 %	58.1
Google Gemini-2.0-Flash-Exp	1.3 %	98.7 %	99.9 %	60
OpenAI-o1-mini	1.4 %	98.6 %	100.0 %	78.3
GPT-4o	1.5 %	98.5 %	100.0 %	77.8
GPT-4o-mini	1.7 %	98.3 %	100.0 %	76.3
GPT-4-Turbo	1.7 %	98.3 %	100.0 %	86.2
GPT-4	1.8 %	98.2 %	100.0 %	81.1
GPT-3.5-Turbo	1.9 %	98.1 %	99.6 %	84.1
DeepSeek-V2.5	2.4 %	97.6 %	100.0 %	83.2
Microsoft Orca-2-13b	2.5 %	97.5 %	100.0 %	66.2
Microsoft Phi-3.5-MoE-instruct	2.5 %	97.5 %	96.3 %	69.7
Intel Neural-Chat-7B-v3-3	2.6 %	97.4 %	100.0 %	60.7
Qwen2.5-7B-Instruct	2.8 %	97.2 %	100.0 %	71
AI21 Jamba-1.5-Mini	2.9 %	97.1 %	95.6 %	74.5
Snowflake-Arctic-Instruct	3.0 %	97.0 %	100.0 %	68.7
Qwen2.5-32B-Instruct	3.0 %	97.0 %	100.0 %	67.9
Microsoft Phi-3-mini-128k-instruct	3.1 %	96.9 %	100.0 %	60.1
OpenAI-o1-preview	3.3 %	96.7 %	100.0 %	119.3
Google Gemini-1.5-Flash-002	3.4 %	96.6 %	99.9 %	59.4
01-AI Yi-1.5-34B-Chat	3.7 %	96.3 %	100.0 %	83.7
Llama-3.1-405B-Instruct	3.9 %	96.1 %	99.6 %	85.7
Microsoft Phi-3-mini-4k-instruct	4.0 %	96.0 %	100.0 %	86.8
Llama-3.3-70B-Instruct	4.0 %	96.0 %	100.0 %	85.3
Microsoft Phi-3.5-mini-instruct	4.1 %	95.9 %	100.0 %	75
Mistral-Large2	4.1 %	95.9 %	100.0 %	77.4
Llama-3-70B-Chat-hf	4.1 %	95.9 %	99.2 %	68.5
Qwen2-VL-7B-Instruct	4.2 %	95.8 %	100.0 %	73.9
Qwen2.5-14B-Instruct	4.2 %	95.8 %	100.0 %	74.8
Qwen2.5-72B-Instruct	4.3 %	95.7 %	100.0 %	80
Llama-3.2-90B-Vision-Instruct	4.3 %	95.7 %	100.0 %	79.8
XAI Grok	4.6 %	95.4 %	100.0 %	91
Anthropic Claude-3-5-sonnet	4.6 %	95.4 %	100.0 %	95.9
Qwen2-72B-Instruct	4.7 %	95.3 %	100.0 %	100.1
Mixtral-8x22B-Instruct-v0.1	4.7 %	95.3 %	99.9 %	92
Anthropic Claude-3-5-haiku	4.9 %	95.1 %	100.0 %	92.9
01-AI Yi-1.5-9B-Chat	4.9 %	95.1 %	100.0 %	85.7
Cohere Command-R	4.9 %	95.1 %	100.0 %	68.7
Llama-3.1-70B-Instruct	5.0 %	95.0 %	100.0 %	79.6
Llama-3.1-8B-Instruct	5.4 %	94.6 %	100.0 %	71
Cohere Command-R-Plus	5.4 %	94.6 %	100.0 %	68.4
Llama-3.2-11B-Vision-Instruct	5.5 %	94.5 %	100.0 %	67.3
Llama-2-70B-Chat-hf	5.9 %	94.1 %	99.9 %	84.9
IBM Granite-3.0-8B-Instruct	6.5 %	93.5 %	100.0 %	74.2
Google Gemini-1.5-Pro-002	6.6 %	93.7 %	99.9 %	62
Google Gemini-1.5-Flash	6.6 %	93.4 %	99.9 %	63.3
Microsoft phi-2	6.7 %	93.3 %	91.5 %	80.8
Google Gemma-2-2B-it	7.0 %	93.0 %	100.0 %	62.2
Qwen2.5-3B-Instruct	7.0 %	93.0 %	100.0 %	70.4
Llama-3-8B-Chat-hf	7.4 %	92.6 %	99.8 %	79.7
Google Gemini-Pro	7.7 %	92.3 %	98.4 %	89.5
01-AI Yi-1.5-6B-Chat	7.9 %	92.1 %	100.0 %	98.9
Llama-3.2-3B-Instruct	7.9 %	92.1 %	100.0 %	72.2
databricks dbrx-instruct	8.3 %	91.7 %	100.0 %	85.9
Qwen2-VL-2B-Instruct	8.3 %	91.7 %	100.0 %	81.8
Cohere Aya Expanse 32B	8.5 %	91.5 %	99.9 %	81.9
IBM Granite-3.0-2B-Instruct	8.8 %	91.2 %	100.0 %	81.6
Mistral-7B-Instruct-v0.3	9.5 %	90.5 %	100.0 %	98.4
Google Gemini-1.5-Pro	9.1 %	90.9 %	99.8 %	61.6
Anthropic Claude-3-opus	10.1 %	89.9 %	95.5 %	92.1
Google Gemma-2-9B-it	10.1 %	89.9 %	100.0 %	70.2
Llama-2-13B-Chat-hf	10.5 %	89.5 %	99.8 %	82.1
AllenAI-OLMo-2-13B-Instruct	10.8 %	89.2 %	100.0 %	82
AllenAI-OLMo-2-7B-Instruct	11.1 %	88.9 %	100.0 %	112.6
Mistral-Nemo-Instruct	11.2 %	88.8 %	100.0 %	69.9
Llama-2-7B-Chat-hf	11.3 %	88.7 %	99.6 %	119.9
Microsoft WizardLM-2-8x22B	11.7 %	88.3 %	99.9 %	140.8
Cohere Aya Expanse 8B	12.2 %	87.8 %	99.9 %	83.9
Amazon Titan-Express	13.5 %	86.5 %	99.5 %	98.4
Google PaLM-2	14.1 %	85.9 %	99.8 %	86.6
Google Gemma-7B-it	14.8 %	85.2 %	100.0 %	113
Qwen2.5-1.5B-Instruct	15.8 %	84.2 %	100.0 %	70.7
Qwen-QwQ-32B-Preview	16.1 %	83.9 %	100.0 %	201.5
Anthropic Claude-3-sonnet	16.3 %	83.7 %	100.0 %	108.5
Google Gemma-1.1-7B-it	17.0 %	83.0 %	100.0 %	64.3
Anthropic Claude-2	17.4 %	82.6 %	99.3 %	87.5
Google Flan-T5-large	18.3 %	81.7 %	99.3 %	20.9
Mixtral-8x7B-Instruct-v0.1	20.1 %	79.9 %	99.9 %	90.7
Llama-3.2-1B-Instruct	20.7 %	79.3 %	100.0 %	71.5
Apple OpenELM-3B-Instruct	24.8 %	75.2 %	99.3 %	47.2
Qwen2.5-0.5B-Instruct	25.2 %	74.8 %	100.0 %	72.6
Google Gemma-1.1-2B-it	27.8 %	72.2 %	100.0 %	66.8
TII falcon-7B-instruct	29.9 %	70.1 %	90.0 %	75.5

Read next:

• WhatsApp Beta Tests Personalized AI Chatbots – A Sneak Peek at What’s Coming!

• Researchers Explore How Personality and Integrity Shape Trust in AI Technology

• China’s AI Chatbot Market Sees ByteDance’s Doubao Leading Through Innovation and Accessibility
by Arooj Ahmed via Digital Information World

WhatsApp Beta Tests Personalized AI Chatbots – A Sneak Peek at What’s Coming!

WhatsApp Beta for Android update is here and as per WBI there is a new feature that is going to create personalized AI chatbots. In the previous update of WhatsApp Beta for Android, a new feature was spotted by WBI, in which Whatsapp tested a dedicated tab for AI powered chats. Due to that feature, users will be able to use AI tools and features conveniently. Now WhatsApp is working on developing AI chats with personalized AI characters. Soon users will be able to create AI chatbots, and can make them unique with specific expertise.

There was a feature available on Instagram of personalizing your AI, but now WhatsApp is bringing it to its own platform with more functionality. This means that users will be able to create their customized AI, meaning, users can bring their own AI ideas to life by creating their tailored AI which will have specific qualities. But our guess is that, it would not be much different from OpenAI's customized instructions.

On Whatsapp AI Chatbot users will have to add a description to their AI character, mentioning what it does and how it is different from other AIs. The AI character can be made of any type, from entertainment and productivity, to a friend or personal assistant. There will also be some options and suggestions for users to choose from if they don't know what type of AI character they want to create.

The descriptions of AI characters that users will provide will be used in shaping the character’s personality. WhatsApp will also ask users to tell what is the main objective and role of their AI character. All of these questions will help WhatsApp create an AI chatbot similar to what users have imagined. Right now, this feature is under development and WhatsApp hasn't made any official announcement about it. So we don't know when this feature will be available to the public.

It is important to note that WhatsApp’s upcoming personalized AI chatbot feature may face delays or never be released, considering Meta’s recent decision to remove its AI personalities from Facebook and Instagram due to backlash.

On the other hand, Meta's privacy practices, especially its use of user data for AI model training, have long raised concerns. The company has faced criticism for its handling of personal information, with many users wary of how their data is utilized for AI development. While caution is advised, careful usage of the new WhatsApp feature is recommended, keeping in mind the potential privacy implications of sharing personal data with AI.

Read next: Social Media’s Youngest Fans: The Platforms Kids Can’t Stay Away From
by Arooj Ahmed via Digital Information World

Researchers Explore How Personality and Integrity Shape Trust in AI Technology

AI has become an important part of our lives and we cannot escape it no matter how hard we try. But the question arises if people trust it enough and if they do, what influences them to make this decision? Researchers from University of Basel conducted a study to find out to what extent do people trust AI chatbots and what factors does it depend upon. For the study, the researchers made up a text based AI platform called Conversea, and analyzed the interactions between the chatbot and the users.

There are a lot of factors that make us trust something. It can be our own personality, how others behave with us, others’ personality and also some specific situation that calls for us to trust someone. The ability of people to trust someone develops from childhood and helps us decide how open we want to be with someone. The researchers say that the factors which play a role in trusting someone also play the same role in our trust in AI systems.

The characteristics most important for trust are integrity and competence and these two help humans evaluate if an AI is reliable or not. The study also found that participants do not think of AI in the light of the company which created it, they think of it as a whole separate unit. Impersonal and personalized chatbots also play a role in our perception of trust in them. If a chatbot is referring to us by our name and also mentions previous conversations, the participants say that the AI chatbot is competent and kind.

When an AI chatbot is personalized, the users think of it as a human and that's why they tend to share more personal information with it and want to use it more. But the study found that there was no difference in trust in personalized and impersonal chatbots by the participants. The study says that for trust to develop, integrity is the most important factor so developing integrity in AI chatbots should be prioritized. Most of the lonely people have started relying on AI because they seem personalized to them.

The researchers of the study said that they think that AI systems should be reliable above anything else. The researchers haven't said anything about whether trusting AI is good or bad, but they think that too much usage of AI as a friend can isolate us from our social environments. AI chatbots should always give advice to users along with the consequences and risks of it. They should also stop inventing answers and just tell the users that they don't have an answer for their question to give them some reality check.

Image: DIW-Aigen

Read next: China’s AI Chatbot Market Sees ByteDance’s Doubao Leading Through Innovation and Accessibility
by Arooj Ahmed via Digital Information World