#NLP AI

[rahulg90]

Smarter Than You Think: NLP-Powered Voice Assistants

Smarter Than You Think: How NLP-Powered Voice Assistants Are Outpacing Human Intelligence Imagine a world where your voice assistant knows your preferences so well that it can predict your needs before you even ask. How close are we to achieving such a seamless interaction? With the global voice assistant market projected to surpass $47 billion by 2032, growing at a CAGR of 26.45%, the future of human-technology interaction is not just promising—it's imminent. By the end of this year, over 8 billion digital voice assistants will be in use worldwide, exceeding the global population. How has this rapid adoption transformed industries, and what innovations lie ahead?

Voice assistants are no longer confined to simple tasks like setting alarms or playing music. They are now integral to complex operations in healthcare, customer service, and smart homes. How did we get here, and what role does Natural Language Processing (NLP) play in this evolution? This article delves into the rise of voice assistants, the groundbreaking advances in NLP, and their real-world applications. We will also explore expert insights and prospects, comprehensively understanding how these technologies reshape our world.

The Rise of Voice Assistants

Voice assistants have evolved from rudimentary voice-activated tools to sophisticated AI-powered systems capable of understanding and processing complex commands. What key milestones have marked this journey, and who are the major players driving this transformation?

Historical Context

The concept of voice-controlled devices dates back to the 1960s with IBM's Shoebox, which could recognize and respond to 16 spoken words. However, it was in the early 2000s that voice assistants began to gain mainstream attention. In 2011, Apple introduced Siri, the first voice assistant integrated into a smartphone, followed by the launch of Google Now in 2012, Microsoft's Cortana in 2013, and Amazon's Alexa in 2014. How have these early versions laid the groundwork for today's advanced voice assistants?

Adoption Metrics

The rapid adoption of voice assistants is reflected in various metrics and statistics. What are the key figures that illustrate this trend?

Market Growth

According to Astute Analytica, the global voice assistant market is expected to reach $47 billion by 2032, growing at a CAGR of 26.45%.

User Engagement

By 2023, the number of voice assistant users in the United States alone hit approximately 125 million, accounting for almost 40% of the population.

Usage Patterns

Voicebot.ai reports that smart speaker owners use their devices for an average of 7.5 tasks, illustrating the diverse applications of voice assistants in everyday life. Furthermore, voice shopping is projected to hit $20 billion in sales by the end of 2023, up from just $2 billion in 2018.

User Engagement

Voice assistants are not just widely adopted; they are also highly engaged. According to Edison Research, 62% of Americans used a voice assistant at least once a month in 2021.

Natural Language Processing: The Backbone of Voice Assistants

Natural Language Processing (NLP) technology allows voice assistants to understand, interpret, and respond to human language. By combining computational linguistics with machine learning and deep learning models, NLP enables machines to process and analyze large amounts of natural language data. The advancements in NLP are pivotal to the sophisticated capabilities of modern voice assistants.

Improved Algorithms and Models

The recent progress in NLP can be attributed to developing advanced algorithms and models that significantly enhance language understanding and generation.

Transformers and BERT

Transformers: Introduced in the paper "Attention is All You Need" by Vaswani et al. (2017), transformers have revolutionized NLP by enabling models to consider the entire context of a sentence simultaneously, which is a significant departure from traditional models that process words sequentially.

BERT (Bidirectional Encoder Representations from Transformers): Developed by Google, BERT allows models to understand the context of a word based on its surrounding words, improving tasks such as question answering and sentiment analysis. Since its release, BERT has become a benchmark in NLP, significantly improving the accuracy of voice assistants. For instance, Google's search engine, powered by BERT, understands queries better, leading to more relevant search results.

OpenAI's GPT-4

With 175 billion parameters, GPT-4 has set new benchmarks in NLP. It can generate human-like text, understand nuanced prompts, and engage in more coherent and contextually relevant conversations. This model is the backbone of many advanced voice assistants, enhancing their ability to generate natural, fluid, and contextually appropriate responses.

Speech Recognition

Accurate speech recognition is critical for the effective functioning of voice assistants. Recent advancements have significantly improved the accuracy and efficiency of speech-to-text conversion.

End-to-End Models

Deep Speech by Baidu: Traditional speech recognition systems involve complex pipelines, but modern end-to-end models like Deep Speech streamline the process, leading to faster and more accurate recognition. These models can process audio inputs directly, converting them into text with minimal latency.

Error Rates: The word error rate (WER) for speech recognition systems has drastically reduced. Google's WER has improved from 23% in 2013 to 4.9% in 2021, making voice assistants more reliable and user-friendly.

Real-World Application

Healthcare

Mayo Clinic uses advanced speech recognition in its patient monitoring systems, allowing doctors to transcribe notes accurately and quickly during consultations. It reduces the administrative burden while enhancing patient care by enabling real-time documentation.

Contextual Understanding

The ability of voice assistants to maintain context and understand the nuances of human language is critical for meaningful interactions.

Context Carryover

Conversational AI: Modern voice assistants can maintain context across multiple interactions. For example, if you ask, "Who is the president of the United States?" followed by "How old is he?", the assistant understands that "he" refers to the president mentioned in the previous query. This ability to carry over context improves the fluidity and coherence of conversations.

Personalization: Assistants like Google Assistant and Amazon Alexa use context to provide personalized responses. They remember user preferences and previous interactions, allowing for a more tailored experience. For instance, if you frequently ask about the weather, the assistant might proactively provide weather updates based on your location and routine.

Sentiment Analysis

Emotional Recognition: Advanced NLP models can detect the sentiment behind a user's request, enabling voice assistants to respond more empathetically. This is particularly useful in customer service applications, where understanding the user's emotional state can lead to better service. For example, if a user sounds frustrated, the assistant might quickly escalate the query to a human representative.

Practical Applications and Impact

The advancements in NLP have broad implications across various industries, significantly enhancing the capabilities and applications of voice assistants.

Healthcare

Voice assistants are revolutionizing healthcare by providing hands-free, voice-activated assistance to medical professionals and patients.

Remote Patient Monitoring

Mayo Clinic uses Amazon Alexa to monitor patients remotely. Patients can report symptoms, receive medication reminders, and access health information through voice commands. This integration has improved patient engagement and adherence to treatment plans.

Surgical Assistance

Voice assistants integrated with AI-powered surgical tools help surgeons access patient data, medical images, and procedural guidelines without leaving the sterile field, reduce surgery time, and enhance precision, ultimately improving patient outcomes.

Customer Service

Companies leverage voice assistants to enhance customer service by providing instant, 24/7 support.

Banking

Bank of America introduced Erica, a virtual assistant that helps customers with tasks like checking balances, transferring money, and paying bills. Since its launch, Erica has handled over 400 million customer interactions, demonstrating the potential of voice assistants in improving customer service efficiency.

E-commerce

Walmarts voice assistant allows customers to add items to their shopping carts, check order statuses, and receive personalized shopping recommendations, enhancing the overall shopping experience. This seamless integration of voice technology in e-commerce platforms increased customer satisfaction and loyalty.

Smart Homes

Voice assistants are central to the smart home ecosystem, enabling users to control devices and manage their homes effortlessly.

Home Automation

Devices like Amazon Echo and Google Nest allow users to control lights, thermostats, and security systems through voice commands. IDC states that smart home device shipments are expected to reach 1.6 billion units by 2023, driven by voice assistant integration.

Energy Management

Companies like Nest Labs use voice assistants to optimize energy consumption by adjusting heating and cooling systems based on user preferences and occupancy patterns. This enhances convenience and leads to significant energy savings and reduced utility bills.

The advancements in NLP have been instrumental in transforming voice assistants from basic tools into sophisticated, AI-powered systems capable of understanding and responding to complex human language. These technologies are now integral to various industries, enhancing efficiency, personalization, and user experience.

Real-Life Applications

The advancements in voice assistants and Natural Language Processing (NLP) have transcended theoretical improvements and are now making a tangible impact across various industries. These technologies, from healthcare and customer service to smart homes, enhance efficiency, user experience, and operational capabilities. This section delves into real-life applications and provides detailed case studies showcasing the transformative power of voice assistants and NLP.

Enhancing Patient Care with Alexa

The Mayo Clinic's integration of Amazon Alexa for remote patient monitoring is a prime example of how voice assistants can improve healthcare delivery. Patients, especially those with chronic conditions, can use Alexa to report their daily symptoms, receive medication reminders, and access educational content about their health conditions. This system has increased patient engagement and provided healthcare providers valuable data to monitor patient health more effectively. The result is a more proactive approach to healthcare, reducing the need for frequent hospital visits and improving overall patient outcomes.

Bank of America: Revolutionizing Banking with Erica

Bank of America's Erica is an AI-driven virtual assistant designed to help customers with everyday banking needs. Erica uses advanced NLP to understand customer queries and provide accurate responses. For example, customers can ask Erica to check their account balance, transfer funds, pay bills, and even receive insights on their spending habits. The virtual assistant has been a game-changer in customer service, handling millions of interactions and significantly reducing the workload on human agents. This has led to improved customer satisfaction and operational efficiency.

Walmart: Streamlining Shopping with Voice Assistants

Walmart's integration of voice assistants into its shopping experience showcases how retail can benefit from this technology. Customers can use voice commands to add items to their shopping carts, check order statuses, and receive personalized shopping recommendations. This functionality is particularly beneficial for busy customers who can manage their shopping lists while multitasking. The result is a more convenient and efficient shopping experience, contributing to increased customer loyalty and sales.

All these examples highlight the transformative power of voice assistants and NLP across various industries. From improving patient care in healthcare to enhancing customer service in banking and retail, these technologies drive significant improvements in efficiency, user experience, and operational capabilities.

Challenges and Ethical Considerations

While the advancements in voice assistants and Natural Language Processing (NLP) are impressive, they also bring several challenges and ethical considerations that must be addressed to ensure their responsible use and deployment.

Privacy and Security

Voice assistants constantly listen for wake words, which raises significant privacy and data security concerns. These devices have microphones that can record conversations without the user's consent, leading to fears about unauthorized data collection and breaches.

Data Collection

Always Listening: Voice assistants must always listen to wake words like "Hey Siri" or "Alexa", which means they continuously record short audio snippets. Although these snippets are usually discarded if the wake word is not detected, there is a risk that they could be accidentally stored and analyzed. According to a survey by Astute Analytica, only 10% of respondents trust that their voice assistant data is secure.

Data Usage: Companies collect voice data to improve the accuracy and functionality of their voice assistants. However, this data can be sensitive and personal, raising concerns about how it is stored, used, and potentially shared. Data breaches, such as the exposure of over 2.8 million recorded voice recordings in 2020, have occurred.

Security Measures

Encryption and Anonymization: To mitigate these risks, companies must implement robust security measures, including encryption and anonymization of voice data. For example, Apple emphasizes using on-device processing for Siri requests, minimizing the data sent to its servers.

Regulations and Compliance: Adhering to data protection regulations such as Europe's General Data Protection Regulation (GDPR) is crucial. These regulations mandate strict data collection, storage, and usage guidelines, protecting user privacy.

Bias and Fairness: NLP models can inadvertently learn and propagate biases in their training data, leading to unfair treatment of certain user groups. Addressing these biases is critical to ensure that voice assistants provide equitable and accurate user interactions.

Training Data Bias

Representation Issues: NLP models are trained on vast datasets that may contain biases reflecting societal prejudices. For example, a study by Stanford University found that major voice recognition systems had an error rate of 20.1% for African American voices compared to 4.9% for white-American voices.

Mitigation Strategies: Companies are developing more inclusive datasets and employing data augmentation and adversarial training techniques to combat these biases. Google and Microsoft have launched initiatives to diversify their training data and improve the fairness of their models.

Algorithmic Fairness

Bias Detection and Correction: Tools and frameworks for detecting and correcting bias in NLP models are becoming increasingly sophisticated. Techniques such as fairness constraints and bias mitigation algorithms help ensure that voice assistants treat all users equitably.

Ethical AI Practices: Implementing ethical AI practices involves regular audits, transparency in algorithm development, and involving diverse teams in creating and testing NLP models. OpenAI and leading AI research organizations advocate for these practices to build more trustworthy and fair AI systems.

Ethical Use and User Consent: The ethical use of voice assistants requires transparency and obtaining informed user consent for data collection and processing.

Transparency

Clear Communication: Companies must communicate how voice data is used, stored, and protected. This includes detailed privacy policies and regular updates to users about changes in data practices.

User Control: It is essential to provide users with control over their data. Options to review, manage, and delete voice recordings should be readily available. Amazon, for example, allows users to delete their voice recordings through the Alexa app.

Informed Consent

Explicit Consent: Users should be explicitly informed about the collected data and its intended use. Clear and concise consent forms and prompts during the voice assistant's initial setup can achieve this.

Opt-In Features: Implementing opt-in features for data sharing, rather than default opt-in, ensures that users actively choose to share their data. This approach respects user autonomy and builds trust.

Future Prospects and Innovation

The future of voice assistants and NLP looks promising, with several innovations on the horizon that promise further to enhance their capabilities and integration into daily life.

Multimodal Interactions

Voice and Visual Integration: Combining voice with visual inputs to provide more comprehensive assistance. For instance, smart displays like Amazon Echo Show and Google Nest Hub use voice and screen interactions to offer richer user experiences. This multimodal approach can provide visual cues, detailed information, and interactive elements that voice alone cannot convey.

Augmented Reality (AR): Future integrations could include AR, where voice commands control AR experiences. For example, users could use voice commands to navigate through AR-enhanced retail environments or educational content, seamlessly blending the physical and digital worlds.

Emotional Intelligence

Sentiment Analysis and Emotional Recognition: Developing voice assistants capable of recognizing and responding to human emotions. This involves advanced sentiment analysis and emotional recognition algorithms, enabling more empathetic interactions. For instance, a voice assistant could detect stress or frustration in a user's voice and offer calming suggestions or escalate the interaction to a human representative.

Personalized Interactions: Emotionally intelligent voice assistants could tailor responses based on the user's emotional state, improving the overall user experience. For example, if a user feels down, the assistant could suggest uplifting music or activities.

Domain-Specific Assistants

Specialized Voice Assistants: Creating voice assistants tailored to specific healthcare, finance, and education industries. These assistants would have deep domain knowledge, providing more accurate and relevant assistance. For instance, a healthcare-specific assistant could offer detailed medical advice and support for chronic disease management, while a finance-specific assistant could provide real-time financial analytics and advice.

Professional Applications: Domain-specific voice assistants could streamline workflows and enhance productivity in professional settings. For example, a legal assistant could help lawyers manage case files, schedule appointments, and provide quick access to legal precedents.

Enhanced Personalization

User Profiles and Preferences: Future voice assistants will increasingly leverage user profiles and preferences to offer personalized experiences. By learning from past interactions, these assistants can predict user needs and preferences, providing proactive assistance. For example, a voice assistant could remind users of upcoming appointments, suggest meal plans based on dietary choices, or provide personalized news updates.

Adaptive Learning: Voice assistants could employ adaptive learning techniques to continually refine their understanding of individual users. This would enable them to improve their accuracy and relevance over time, offering a more tailored and effective user experience.

Improved Accessibility

Inclusive Design: Innovations in voice assistants aim to improve accessibility for individuals with disabilities. For instance, voice assistants can help visually impaired users navigate their devices and environments more easily. Additionally, speech-to-text and text-to-speech can assist users with hearing or speech impairments.

Language and Dialect Support: Enhancing the ability of voice assistants to understand and respond to a wider range of languages and dialects, including major global languages, regional dialects, and minority languages, will make voice assistants more inclusive and accessible to diverse populations.

Concluding Thoughts

The advancements in voice assistants and NLP are not just incremental improvements but transformative shifts reshaping how we interact with technology. From enhancing healthcare delivery and customer service to revolutionizing smart homes and professional applications, the impact of these technologies is profound and far-reaching. However, as we continue integrating voice assistants into more aspects of our lives, addressing the associated challenges and ethical considerations is crucial. Ensuring data privacy and security, mitigating biases in NLP models, and maintaining transparency and user consent are essential for these technologies' responsible development and deployment.

[karasutoragara]

お題: 暑くて食欲が出ないです。家族はお肉が好きです。メニュー浮かばないので、簡単に作れてスタミナのつく夕食のメニューを提案して。

Bard

暑くて食欲がでない時は、さっぱりとした味付けで、食べやすい食材を選ぶと良いでしょう。また���家族皆が好きなお肉をメインにすると、食欲もアップしやすくなります。

そこで、以下のようなメニューはいかがでしょうか。

**メイン**

* 豚バラ肉の照り焼き丼

* 鶏むね肉と野菜のソテー

* 牛肉のすき焼き

* 豚肉のスタミナ炒め

**副菜**

* キャベツとツナのサラダ

* きゅうりの浅漬け

* トマトサラダ

* 冷奴

**汁物**

* 冷たい味噌汁

* 冷やしうどん

* 冷やし中華

**デザート**

* フルーツ

* アイスクリーム

これらのメニューは、どれも簡単に作れるので、暑い日にぴったりです。また、お肉をメインにすることで、スタミナをつけることができます。

**豚バラ肉の照り焼き丼**

豚バラ肉を照り焼きにして、ご飯にのせるだけの簡単レシピです。甘辛いタレがご飯によく絡んで、食欲がなくても思わず食べてしまう美味しさです。

**鶏むね肉と野菜のソテー**

鶏むね肉と野菜をソテーするだけの簡単レシピです。鶏むね肉はさっぱりとした味付けなので、暑い日でも食べやすいです。

**牛肉のすき焼き**

牛肉と野菜を甘辛いタレで煮込んだ定番のスタミナ料理です。家族皆で楽しく食べられるメニューです。

**豚肉のスタミナ炒め**

豚肉、キャベツ、ニラ、にんにくなどの具材を炒めたスタミナ炒めです。ご飯にのせて食べれば、ボリューム満点のおかずになります。

**キャベツとツナのサラダ**

キャベツとツナ、マヨネーズを和えたさっぱりとしたサラダです。暑い日にぴったりのメニューです。

**きゅうりの浅漬け**

きゅうりを塩漬けにした定番の浅漬けです。さっぱりとした味わいで、食欲をそそります。

**トマトサラダ**

トマト、きゅうり、玉ねぎなどの野菜を和えたサラダです。トマトのさっぱりとした酸味が、暑い日にぴったりです。

**冷奴**

豆腐を湯通しして、ネギやポン酢などで味付けしたメニューです。暑い日にぴったりのヘルシーなおかずです。

**冷たい味噌汁**

冷たい水で作った味噌汁です。暑い日にぴったりのさっぱりとした味わいです。

**冷やしうどん**

うどんを茹でて、冷水でしめた後、お好みの具材とタレをかけたメニューです。暑い日にぴったりのさっぱりとした麺料理です。

**冷やし中華**

麺を茹でて、冷水でしめた後、お好みの具材とタレをかけたメニューです。暑い日にぴったりのさっぱりとした麺料理です。

**フルーツ**

旬のフルーツをそのまま食べたり、ヨーグルトやアイスクリームと合わせて食べたりするのがおすすめです。

**アイスクリーム**

暑い日にぴったりの冷たいデザートです。お好みのアイスクリームを召し上がれ。

このメニューを参考に、ご家族で美味しくスタミナをつけられる夕食を作ってみてください。

ChatGPT Plus

暑い日には、さっぱりとした味付けのお肉料理がお勧めです。以下のメニューは簡単に作れて、家族も喜ぶかもしれません：

1. **冷しゃぶサラダ**

- 豚肉を茹でて冷ます。

- サラダ野菜と一緒に盛り付け、ポン酢やごまドレッシングをかける。

2. **鶏むね肉のガーリックソテー**

- 鶏むね肉に塩、胡椒を振っておき、フライパンでソテーします。

- ガーリックスライスを加え、さっと炒めます。

- レモン汁をかけてさっぱりとした味付けに。

3. **焼き肉風ビーフサラダ**

- お好みの部位の牛肉を薄くスライスし、焼きます。

- 野菜と一緒に盛り付け、焼き肉の��レで食べます。

4. **鶏肉の生姜焼き**

- 鶏もも肉や鶏むね肉を使用します。

- 生姜、醤油、みりんで作ったタレに漬け込み、フライパンで焼きます。

- ご飯と一緒に食べれば、スタミナアップに！

以上のようなメニューは比較的短時間で作れ、さっぱりとした味付けが特徴です。お試し下さい！

Bing

食欲が出ないときは、さっぱりとしたものやスパイシーなものがおすすめです。お肉が好きな家族にも喜ばれる簡単に作れてスタミナのつく夕食のメニューをいくつか提案しますね。

- 酸味でさっぱり。 梅しそベーゼそうめん¹：そうめんに梅干しと大葉を合わせたアーモンドベーゼをかけるだけで、暑い日にぴったりの一品になります。アーモンドはすりつぶしてもよいですし、市販のアーモンドペーストを使ってもOKです。

- レンジでOK。 ラー油ぶっかけ肉玉冷やしうどん¹：豚しゃぶしゃぶ用の肉とニラをレンジで加熱して、冷やしうどんにのせてラー油をかけるだけで、ピリ辛でスタミナがつくメニューになります。卵黄を添えても美味しいですよ。

- さっぱり冷麺風！ 長芋そうめん¹：長芋を千切りにしてそうめん風に見立てる、一風変わった冷麺です。酸味がさわやかな冷麺風スープをかけて、さらっとのど越しのよい長芋冷麺をお召し上がりください。

- 暑い日はさっぱりレモンレシピ！ レモポン炒め²：豚こまとキャベツのレモポン炒めは、下ごしらえの工程も少なく、炒める時間も少なくてすむ暑い日におすすめのメニューです。ポン酢とレモンの味が爽やかな炒め物です。

- 暑い日は冷たいおかず！ 南蛮漬け³：揚げた魚や肉と野菜を、酢をきかせた漬け汁に浸した料理です。酢の効果でさっぱりと食べられるので、暑い日の夕飯におすすめです。作り置きにもできますよ。

以上、暑くて食欲が出ない日にもおすすめの簡単に作れてスタミナのつく夕食のメニューをご紹介しました。どれも手軽に作れるレシピなので、ぜひ試してみてくださいね。

ソース: Bing との会話 2023/9/5

(1) 暑い夏におすすめの夕飯レシピ27選！さっぱり系からスタミナ系 .... https://macaro-ni.jp/76245.

(2) 暑い日の夕飯レシピ特集！食欲がない日にもおすすめの .... https://folk-media.com/2481000.

(3) 暑い日の夕飯は簡単にしたい！さっぱり〜スタミナレシピ23選の .... https://delishkitchen.tv/curations/4480.

(4) 暑い日に食べたい！さっぱりおかず&スタミナ料理のレシピ集 .... https://kinarino.jp/cat4/13467.

[yawpyawp]

one of my projects at work right now is to design an icon for an AI chatbot and this is my latest draft:

[gnosticgnoob]

I would have painted this myself but I didn't have to

[varundigital]

The digital world is evolving fast, and #SEO and #AEO are at the forefront of this change! SEO still reigns as the king of driving organic traffic, and it's all about ranking higher for the right keywords. But don't forget, AEO (Answer Engine Optimization) is making waves too with a fresh approach:

Answer-Based Searches

Voice-Based Queries

AI & NLP The shift is happening, and it’s time to adapt! Are you ready for both? 👉 🌐 www.varundigitalmedia.com 👉 📧 info@varundigitalmedia.com 👉 📲 (+1) 877-768-2786

[abathurofficial]

Abathur

At Abathur, we believe technology should empower, not complicate.

Our mission is to provide seamless, scalable, and secure solutions for businesses of all sizes. With a team of experts specializing in various tech domains, we ensure our clients stay ahead in an ever-evolving digital landscape.

Why Choose Us? Expert-Led Innovation – Our team is built on experience and expertise. Security First Approach – Cybersecurity is embedded in all our solutions. Scalable & Future-Proof – We design solutions that grow with you. Client-Centric Focus – Your success is our priority.

[futuretiative]

Tom and Robotic Mouse | @futuretiative

Tom's job security takes a hit with the arrival of a new, robotic mouse catcher.

TomAndJerry #AIJobLoss #CartoonHumor #ClassicAnimation #RobotMouse #ArtificialIntelligence #CatAndMouse #TechTakesOver #FunnyCartoons #TomTheCat

Keywords: Tom and Jerry, cartoon, animation, cat, mouse, robot, artificial intelligence, job loss, humor, classic, Machine Learning Deep Learning Natural Language Processing (NLP) Generative AI AI Chatbots AI Ethics Computer Vision Robotics AI Applications Neural Networks

Tom was the first guy who lost his job because of AI

(and what you can do instead)

⤵

"AI took my job" isn't a story anymore.

It's reality.

But here's the plot twist:

While Tom was complaining,

others were adapting.

The math is simple:

➝ AI isn't slowing down

➝ Skills gap is widening

➝ Opportunities are multiplying

Here's the truth:

The future doesn't care about your comfort zone.

It rewards those who embrace change and innovate.

Stop viewing AI as your replacement.

Start seeing it as your rocket fuel.

Because in 2025:

➝ Learners will lead

➝ Adapters will advance

➝ Complainers will vanish

The choice?

It's always been yours.

It goes even further - now AI has been trained to create consistent.

//

Repost this ⇄

//

Follow me for daily posts on emerging tech and growth

[plus27digital]

Artificial Intelligence in Digital Marketing: Definition and Tools

AI in digital marketing refers to employing intelligent technologies to enhance how businesses engage with and sell to their customers. Assists with data management, automation, customization, and refinement of campaigns. But what exactly does AI do in marketing? It uses machine learning, data analysis, and natural language processing to perform tasks faster and more accurately than humans.

Many make use of AI to simplify marketing. Customer service chatbots respond to clients in seconds. Tools using predictive analytics make it easier for businesses to grasp future shifts. Some programs are capable of generating content for blogs, emails, and even product descriptions. Messages intended for particular customers can be tailored through personalization platforms, making them more appealing. Marketing automation tools streamline tedious processes such as email dispatching and advertising, thereby cutting down on time and effort.

AI enhances digital ads as well. It modifies cost-per-click bids, targets audiences, and adjusts creatives simultaneously in order for businesses to derive the most benefit. Sentiment analysis tools automatically filter and analyze social media channels and online reviews to assess client’s’ perceptions. Customer segmentation tools analyze persona’s behavior to aggregate them into more manageable groups, thus enhancing campaign efficiency.

What are the advantages? AI saves labor in completing repetitive tasks. It provides businesses with comprehensive insights, assisting in making better decisions. It delivers content at scale and enhances the customer experience by providing tailored suggestions. It even has the capacity to determine trends, which is advantageous for businesses.

AI can, however, contain imperfections. If an algorithm is trained using biased data, it may contain biases. Misinformation in AI-generated content can lead to erroneous information being disseminated to customers. There are issues of privacy and security with a significant amount of data. Some people are concerned with the issue of transparency—who owns the content generated by AI?

AI is evolving in digital marketing, creating new opportunities and difficulties at the same time. To remain relevant in today's society, engaging with professionals is the best way to go. PLUS27digital specializes in AI-based marketing strategy development that deliver incredible outcomes. Would you like to learn how AI could improve your business? Let's have a discussion.

[fraoula1]

𝐌𝐢𝐬𝐭𝐫𝐚𝐥 𝐀𝐈 𝐋𝐞 𝐂𝐡𝐚𝐭: 𝐓𝐡𝐞 𝐅𝐚𝐬𝐭𝐞𝐬𝐭 𝐀𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭 𝐄𝐯𝐞𝐫? 1,000 𝐖𝐨𝐫𝐝𝐬 𝐏𝐞𝐫 𝐒𝐞𝐜𝐨𝐧𝐝!

Mistral AI has unveiled Le Chat, an incredibly fast AI assistant capable of processing 1,000 words per second! 🚀 This groundbreaking technology is set to revolutionize virtual assistants with lightning-fast responses, advanced language understanding, and seamless multitasking.

In this video, we explore:

✅ How speed enhances AI assistance

✅ Key features like natural language understanding & multitasking

✅ The benefits of Le Chat for productivity, customer support, and education

✅ What the future holds for AI-powered assistants

Watch https://youtube.com/shorts/ohR_-V6g9R0

🔔 Subscribe for the latest AI innovations!

[mysocial8onetech]

Learn how Mistral-NeMo-Minitron 8B, a collaboration between NVIDIA and Mistral AI, is revolutionizing Large Language Models (LLMs). This Open-Source model uses advanced pruning & distillation techniques to achieve top accuracy on 9 benchmarks while being highly efficient.

[riazhatvi]

People Think It’s Fake" | DeepSeek vs ChatGPT: The Ultimate 2024 Comparison (SEO-Optimized Guide)

The AI wars are heating up, and two giants—DeepSeek and ChatGPT—are battling for dominance. But why do so many users call DeepSeek "fake" while praising ChatGPT? Is it a myth, or is there truth to the claims? In this deep dive, we’ll uncover the facts, debunk myths, and reveal which AI truly reigns supreme. Plus, learn pro SEO tips to help this article outrank competitors on Google!

Chapters

00:00 Introduction - DeepSeek: China’s New AI Innovation

00:15 What is DeepSeek?

00:30 DeepSeek’s Impressive Statistics

00:50 Comparison: DeepSeek vs GPT-4

01:10 Technology Behind DeepSeek

01:30 Impact on AI, Finance, and Trading

01:50 DeepSeek’s Effect on Bitcoin & Trading

02:10 Future of AI with DeepSeek

02:25 Conclusion - The Future is Here!

Why Do People Call DeepSeek "Fake"? (The Truth Revealed)

The Language Barrier Myth

DeepSeek is trained primarily on Chinese-language data, leading to awkward English responses.

Example: A user asked, "Write a poem about New York," and DeepSeek referenced skyscrapers as "giant bamboo shoots."

SEO Keyword: "DeepSeek English accuracy."

Cultural Misunderstandings

DeepSeek’s humor, idioms, and examples cater to Chinese audiences. Global users find this confusing.

ChatGPT, trained on Western data, feels more "relatable" to English speakers.

Lack of Transparency

Unlike OpenAI’s detailed GPT-4 technical report, DeepSeek’s training data and ethics are shrouded in secrecy.

LSI Keyword: "DeepSeek data sources."

Viral "Fail" Videos

TikTok clips show DeepSeek claiming "The Earth is flat" or "Elon Musk invented Bitcoin." Most are outdated or edited—ChatGPT made similar errors in 2022!

DeepSeek vs ChatGPT: The Ultimate 2024 Comparison

1. Language & Creativity

ChatGPT: Wins for English content (blogs, scripts, code).

Strengths: Natural flow, humor, and cultural nuance.

Weakness: Overly cautious (e.g., refuses to write "controversial" topics).

DeepSeek: Best for Chinese markets (e.g., Baidu SEO, WeChat posts).

Strengths: Slang, idioms, and local trends.

Weakness: Struggles with Western metaphors.

SEO Tip: Use keywords like "Best AI for Chinese content" or "DeepSeek Baidu SEO."

2. Technical Abilities

Coding:

ChatGPT: Solves Python/JavaScript errors, writes clean code.

DeepSeek: Better at Alibaba Cloud APIs and Chinese frameworks.

Data Analysis:

Both handle spreadsheets, but DeepSeek integrates with Tencent Docs.

3. Pricing & Accessibility

FeatureDeepSeekChatGPTFree TierUnlimited basic queriesGPT-3.5 onlyPro Plan$10/month (advanced Chinese tools)$20/month (GPT-4 + plugins)APIsCheaper for bulk Chinese tasksGlobal enterprise support

SEO Keyword: "DeepSeek pricing 2024."

Debunking the "Fake AI" Myth: 3 Case Studies

Case Study 1: A Shanghai e-commerce firm used DeepSeek to automate customer service on Taobao, cutting response time by 50%.

Case Study 2: A U.S. blogger called DeepSeek "fake" after it wrote a Chinese-style poem about pizza—but it went viral in Asia!

Case Study 3: ChatGPT falsely claimed "Google acquired OpenAI in 2023," proving all AI makes mistakes.

How to Choose: DeepSeek or ChatGPT?

Pick ChatGPT if:

You need English content, coding help, or global trends.

You value brand recognition and transparency.

Pick DeepSeek if:

You target Chinese audiences or need cost-effective APIs.

You work with platforms like WeChat, Douyin, or Alibaba.

LSI Keyword: "DeepSeek for Chinese marketing."

SEO-Optimized FAQs (Voice Search Ready!)

"Is DeepSeek a scam?" No! It’s a legitimate AI optimized for Chinese-language tasks.

"Can DeepSeek replace ChatGPT?" For Chinese users, yes. For global content, stick with ChatGPT.

"Why does DeepSeek give weird answers?" Cultural gaps and training focus. Use it for specific niches, not general queries.

"Is DeepSeek safe to use?" Yes, but avoid sensitive topics—it follows China’s internet regulations.

Pro Tips to Boost Your Google Ranking

Sprinkle Keywords Naturally: Use "DeepSeek vs ChatGPT" 4–6 times.

Internal Linking: Link to related posts (e.g., "How to Use ChatGPT for SEO").

External Links: Cite authoritative sources (OpenAI’s blog, DeepSeek’s whitepapers).

Mobile Optimization: 60% of users read via phone—use short paragraphs.

Engagement Hooks: Ask readers to comment (e.g., "Which AI do you trust?").

Final Verdict: Why DeepSeek Isn’t Fake (But ChatGPT Isn’t Perfect)

The "fake" label stems from cultural bias and misinformation. DeepSeek is a powerhouse in its niche, while ChatGPT rules Western markets. For SEO success:

Target long-tail keywords like "Is DeepSeek good for Chinese SEO?"

Use schema markup for FAQs and comparisons.

Update content quarterly to stay ahead of AI updates.

🚀 Ready to Dominate Google? Share this article, leave a comment, and watch it climb to #1!

Follow for more AI vs AI battles—because in 2024, knowledge is power! 🔍

[govindhtech]

Benefits Of Conversational AI & How It Works With Examples

What Is Conversational AI?

Conversational AI mimics human speech. It’s made possible by Google’s foundation models, which underlie new generative AI capabilities, and NLP, which helps computers understand and interpret human language.

How Conversational AI works

Natural language processing (NLP), foundation models, and machine learning (ML) are all used in conversational AI.

Large volumes of speech and text data are used to train conversational AI systems. The machine is trained to comprehend and analyze human language using this data. The machine then engages in normal human interaction using this information. Over time, it improves the quality of its responses by continuously learning from its interactions.

Conversational AI For Customer Service

With IBM Watsonx Assistant, a next-generation conversational AI solution, anyone in your company can easily create generative AI assistants that provide customers with frictionless self-service experiences across all devices and channels, increase employee productivity, and expand your company.

User-friendly: Easy-to-use UI including pre-made themes and a drag-and-drop chat builder.

Out-of-the-box: Unconventional To better comprehend the context of each natural language communication, use large language models, large speech models, intelligent context gathering, and natural language processing and understanding (NLP, NLU).

Retrieval-augmented generation (RAG): It based on your company’s knowledge base, provides conversational responses that are correct, relevant, and current at all times.

Use cases

Watsonx Assistant may be easily set up to accommodate your department’s unique requirements.

Customer service

Strong client support With quick and precise responses, chatbots boost sales while saving contact center funds.

Human resources

All of your employees may save time and have a better work experience with HR automation. Questions can be answered by staff members at any time.

Marketing

With quick, individualized customer service, powerful AI chatbot marketing software lets you increase lead generation and enhance client experiences.

Features

Examine ways to increase production, enhance customer communications, and increase your bottom line.

Artificial Intelligence

Strong Watsonx Large Language Models (LLMs) that are tailored for specific commercial applications.

The Visual Builder

Building generative AI assistants using to user-friendly interface doesn’t require any coding knowledge.

Integrations

Pre-established links with a large number of channels, third-party apps, and corporate systems.

Security

Additional protection to prevent hackers and improper use of consumer information.

Analytics

Comprehensive reports and a strong analytics dashboard to monitor the effectiveness of conversations.

Self-service accessibility

For a consistent client experience, intelligent virtual assistants offer self-service responses and activities during off-peak hours.

Benfits of Conversational AI

Automation may save expenses while boosting output and operational effectiveness.

Conversational AI, for instance, may minimize human error and expenses by automating operations that are presently completed by people. Increase client happiness and engagement by providing a better customer experience.

Conversational AI, for instance, may offer a more engaging and customized experience by remembering client preferences and assisting consumers around-the-clock when human agents are not present.

Conversational AI Examples

Here are some instances of conversational AI technology in action:

Virtual agents that employ generative AI to support voice or text conversations are known as generative AI agents.

Chatbots are frequently utilized in customer care applications to respond to inquiries and offer assistance.

Virtual assistants are frequently voice-activated and compatible with smart speakers and mobile devices.

Software that converts text to speech is used to produce spoken instructions or audiobooks.

Software for speech recognition is used to transcribe phone conversations, lectures, subtitles, and more.

Applications Of Conversational AI

Customer service: Virtual assistants and chatbots may solve problems, respond to frequently asked questions, and offer product details.

E-commerce: Chatbots driven by AI can help customers make judgments about what to buy and propose products.

Healthcare: Virtual health assistants are able to make appointments, check patient health, and offer medical advice.

Education: AI-powered tutors may respond to student inquiries and offer individualized learning experiences.

In summary

The way to communicate with robots might be completely changed by the formidable technology known as conversational AI. Also can use its potential to produce more effective, interesting, and customized experiences if it comprehend its essential elements, advantages, and uses.

Read more on Govindhech.com

[karasutoragara]

お題

Bingが物凄く調べて回答してくれるから、内容の正確性の他に要約をChatGPT（GPT-4）に頼むメソッド。

他者に説明する際に親切かと。

ChatGPT

①このまとめは、NetflixとAmazonプライムビデオの背景、特徴、戦略について詳細に説明しています。そして、NHKやBBCとの比較を通じて、両サービスの投資規模や戦略の違いを強調しています。全体として、内容は妥当と言えます。

②過不足を補って：

- NetflixとAmazonプライムビデオの競合として、他の大手動画配信サービス（例：Disney+やHulu）��簡単な触れ込みがあっても良いかもしれません。

- 会員数やシェアに関するデータが2021年のものであるため、最新のデータやトレンドとの相違があるかもしれません。確認と更新が必要です。

- NHKやBBCのコンテンツ制作予算の説明については、彼らの主な収入源や使命（公共放送としての役割）に関する情報をもう少し詳しく説明すると、比較がより明確になるかもしれません。

③最小限の文字数に要点をまとめて：

Netflixは1997年創業で、現在世界で最も利用される動画配信サービスの一つ。2021年の有料会員数は約2億970万人。AmazonプライムビデオはAmazonのサービスの一部で、2021年の会員数は2億人超。両者はオリジナルコンテンツ制作に大きな投資を行い、それぞれの特色や戦略で競争している。NHKやBBCとの比較では、NetflixとAmazonの制作予算は圧倒的に大きい。

Bing

Netflixは、1997年にアメリカでDVDレンタルサービスとして創業した企業です。2007年には動画ストリーミングサービスに進出し、世界中の視聴者に多様なコンテンツを提供するようになりました。現在、Netflixは世界で最も利用されている動画配信サービスの一つで、2021年第2四半期末時点での有料会員数は2億970万人に達しています¹。Netflixの世界シェアは約20％と推定されており²、アメリカ、ブラジル、イギリスなどの主要市場で高い人気を誇っています。

Amazonプライムビデオは、Amazonが提供する動画ストリーミングサービスです。Amazonプライム会員になると、追加料金なしでプライムビデオのコンテンツを視聴することができます。プライムビデオは2006年にアメリカで開始され、その後世界各国に展開されました。2021年第2四半期末時点でのAmazonプライム会員数は2億人を超えており³、そのうち約半数がプライムビデオを利用していると推測されます⁴。Amazonプライムビデオの世界シェアは約16％と推定されており²、日本、インド、ドイツなどの市場で高いシェアを獲得しています。

NetflixとAmazonプライムビデオは、文化や狙い（ターゲット層など）の面でいくつかの違いがあります。まず、Netflixは動画配信サービスが主力事業であり、そのために多額の投資を行っています。一方、AmazonプライムビデオはAmazonの総合的な会員制サービスの一部であり、動画配信だけでなく、送料無料や音楽配信などの特典も提供しています。そのため、Amazonプライムビデオは動画配信サービスとしてだけではなく、Amazonのエコシステムの一環として評価されるべきです。

また、NetflixとAmazonプライムビデオは、オリジナルコンテンツの制作方針や戦略にも違いがあります。Netflixはオリジナルコンテンツに強く力を入れており、2021年には170億ドル（約1兆9000億円）以上をオリジナルコンテンツの制作費用に充てる予定です⁵。Netflixのオリジナルコンテンツは多様で斬新であり、エミー賞やアカデミー賞などの権威ある賞にも多数ノミネートされています。Netflixは自社制作のコンテンツを全世界に同時配信することで、グロー��ルなブランド力やファン層を築いています。

一方、Amazonプライムビデオもオリジナルコンテンツに注力しており、2021年には80億ドル（約9000億円）以上をオリジナルコンテンツの制作費用に充てる予定です⁶。Amazonプライムビデオのオリジナルコンテンツも高品質で評価されており、ゴールデングローブ賞やアカデミー賞などの賞にもノミネートされています。Amazonプライムビデオは地域ごとに異なるコンテンツを提供することで、ローカルなニーズや嗜好に応えています。また、Amazonプライムビデオは映画館との連携やスポーツ中継の権利の獲得など、他の動画配信サービスとは異なる取り組みも行っています。

NHKやBBCと比較すると、NetflixとAmazonプライムビデオはオリジナルコンテンツの制作費用において圧倒的な規模を誇っています。NHKは2020年度に約6000億円⁷、BBCは2019年度に約4000億円⁸をコンテンツの制作費用に充てていますが、これらはNetflixやAmazonプライムビデオの半分以下です。NHKやBBCは公共放送として受信料や税金などで賄われており、その使途や範囲に制限があります。一方、NetflixやAmazonプライムビデオは民間企業として会員料や広告収入などで資金を調達しており、より自由にコンテンツの制作や配信を行うことができます。

以上のように、NetflixとAmazonプライムビデオはそれぞれに特徴や強みを持った動画配信サービスです。両者は競合関係にありながらも、互いに刺激し合ってコンテンツの質や量を向上させています。今後もNetflixとAmazonプライムビデオの動向に注目していきたいですね。

ソース: Bing との会話 2023/8/16

(1) How to see viewing history and device activity - Netflix. https://help.netflix.com/en/node/101917

(2) Netflix - Wikipedia. https://en.wikipedia.org/wiki/Netflix

(3) Netflix | Founders, History, Shows, & Facts | Britannica. https://www.britannica.com/topic/Netflix-Inc

(4) Netflix – statistics & facts | Statista. https://www.statista.com/topics/842/netflix/

(5) Netflix Revenue and Usage Statistics (2023) - Business of Apps. https://www.businessofapps.com/data/netflix-statistics/

(6) Netflix Market Share | T4. https://www.t4.ai/companies/netflix-market-share

(7) JustWatch: Netflix Third-Quarter Market Share Remains .... https://www.mediaplaynews.com/justwatch-netflix-third-quarter-market-share-remains-tops-among-u-s-streamers-despite-sub-losses/

(8) Japan streaming market share analysis Q2 2021: Netflix .... https://www.parrotanalytics.com/insights/streaming-wars-who-is-winning-japan-q2-2021/

(9) 日本の動画配信市場の現状と将来展望 - Deloitte US. https://www2.deloitte.com/jp/ja/pages/technology-media-and-telecommunications/articles/digital-consumer-trends-2021-japanese-vod-market.html

(10) Streaming in Japan - statistics & facts | Statista. https://www.statista.com/topics/6015/streaming-in-japan/

(11) HISTORY - アマゾン. https://www.amazon.co.jp/gp/video/offers?benefitId=historych

(12) Amazonプライム「ヒストリーチャンネル」解約忘れで失敗しない .... https://a4050life.com/amazon-prime-history-channel/

(13) How to View and Delete Your Amazon Prime Video Watch .... https://bing.com/search?q=Amazon+Prime+Video+history

(14) How to Delete Your Amazon Prime Video History. https://www.howtogeek.com/360484/how-to-delete-your-amazon-prime-video-history/

(15) Amazonプライムビデオの視聴履歴を削除する方法 | アプリオ. https://appllio.com/how-to-delete-viewing-history-of-amazon-prime-video

(16) Amazon Prime Video - statistics & facts | Statista. https://www.statista.com/topics/4740/amazon-prime-video/

(17) 日本のSVOD市場、会員数はAmazon Prime Videoがリード. https://eiga.com/news/20211007/9/

(18) Apple TV+ global market share surpasses 6% - 9to5Mac. https://9to5mac.com/2022/09/06/apple-tv-global-market-share-surpasses-6/

(19) Amazon Leading in Japan’s Booming SVoD Market, Study .... https://variety.com/2021/global/asia/amazon-japan-streaming-svod-market-1235080084/

(20) Amazon Beating Netflix, Disney+ in Japan’s Streaming .... https://www.hollywoodreporter.com/business/business-news/amazon-leads-netflix-disney-in-japan-streaming-1235025531/

(21) A Comparative Analysis of Over-the-Top Platforms: Amazon .... https://link.springer.com/chapter/10.1007/978-981-15-3325-9_22

(22) Brand Personality of Streaming Platforms in 2020: Netflix Vs .... https://www.pulsarplatform.com/blog/2020/how-have-perceptions-of-netflix-amazon-prime-video-and-disney-changed/

(23) Netflix vs Amazon Prime Video: which streaming service is .... https://www.techradar.com/news/netflix-vs-amazon-prime-video-2021

(24) Amazon ramped up content spending to $16.6B in 2022 .... https://techcrunch.com/2023/02/03/amazon-ramped-up-content-spending-to-16-6b-in-2022-including-7b-on-originals/

(25) Amazon: content spend worldwide 2023 | Statista. https://www.statista.com/statistics/738421/amazon-video-content-budget/

(26) NHKと同じ公共放送BBC、受信料制度見直し論の中で“デジタル .... https://www.yomiuri.co.jp/culture/tv/20220714-OYT1T50184/

(27) NHKにも影響？BBC｢受信料制度見直し｣の意味 イギリス政府の .... https://toyokeizai.net/articles/-/587008

(28) 「NHKのネット進出を阻む“枷”を外してから議論すべき .... https://times.abema.tv/articles/-/10022630

上記回答用プロンプト

Netflixの沿革・世界シェア・日本シェア、Amazonプライムとの文化や狙い（ターゲット層など）の違いを解説して。また、両サービスがオリジナル番組を作ることができる、予算の規模をNHKやBBCと比較して。

✅別の話題

ChatGPT

①上記まとめの過不足を整えて：

【動画配信サービス】

メリット：

- 豊富なジャンル・高画質での配信

- 便利な視聴機能と語学学習向けの選択

デメリット：

- 月額・年額料金

- 見たい作品の不定期な配信・視聴制限

情報源の質：

- プロ制作による高品質動画が中心

- 但し、サービスごとの独自の傾向がある

【無料動画サイト】

メリット：

- 無料利用・ユーザー投稿の多様性

デメリット：

- 広告表示・画質のばらつき・著作権の問題

情報源の質：

- ユーザー作成の動画が中心で信頼性にばらつき

②最小限の文字数に要約して：

動画配信サービスは月額料金で豊富な高品質動画を提供、但し内容がサービス依存。無料動画サイトは無料でユーザーの投稿が中心、但し画質や信頼性にばらつき。

Bing

こんにちは、これはBingです。動画配信サービスと無料動画サイトの違いについてお答えします。

動画配信サービスとは、月額や年額の料金を支払って、映画やドラマなどの動画を見放題で楽しめるサービスのことです。NetflixやAmazonプライムビデオなどが有名です。無料動画サイトとは、YouTubeやTVerなどのように、ユーザーが投稿した動画やテレビ番組などの動画を無料で視聴できるサイトのことです。

それぞれのメリット・デメリット・情報源の質や偏りについては、以下のようになります。

【動画配信サービス】

メリット：

- 最新作やオリジナル作品など、豊富なジャンルとラインナップが楽しめる

- 高画質や4Kなど、画質や音質が優れている

- ダウンロード機能や同時視聴機能など、便利な機能が充実している

- 字幕や吹き替えなど、言語選択が可能で語学学習にも役立つ

デメリット：

- 料金がかかる

- 作品の入れ替わりが激しく、見たい作品が配信されていない場合もある

- 見放題ではない作品もあり、追加料金が発生する場合もある

- 著作権の問題で一部の国や地域では視聴できない場合もある

情報源の質や偏り：

- 一般的には、プロの制作チームによって作られた高品質な動画が多い

- しかし、配信サービスごとに独自の傾向や方針があり、特定のジャンルや視点に偏っている場合もある

- 例えば、Netflixはオリジナル作品に力を入れており、韓国ドラマや社会問題を扱ったドキュメンタリーなどが多い²

- AmazonプライムビデオはAmazonの他のサービスと連携しており、音楽や電子書籍なども楽しめるが、レンタル・購入作品も多く含まれている³

【無料動画サイト】

メリット：

- 無料で利用できる

- ユーザー投稿の動画やテレビ番組など、幅広い種類の動画が見られる

- コメント機能や評価機能など、コミュニケーションが取れる

デメリット：

- 広告が多く表示される

- 画質や音質が低い場合がある

- 違法アップロードされた動画もあり、著作権侵害に関わる可能性がある

- 動画の削除や規制が行われる場合がある

情報源の質や偏り：

- 一般的には、ユーザー自身が作成した個人的な動画が多い

- しかし、事実と異なる内容や誤った情報を含む動画もあり、信頼性に欠ける場合もある

- 例えば、YouTubeはニュースや教育などのカテゴリーもあるが、フェイクニュースや陰謀論などの動画も混在している¹

- TVerはテレビ局が運営しており、テレビ番組の見逃し配信ができるが、放送局によって配信される番組や期間が異なる

以上が、動画配信サービスと無料動画サイトの違いについての解説です。どちらもメリット・デメリットがありますので、自分の視聴目的や予算に合わせて選択することが大切です。また、複数のサービスを併用することで、より多くの動画を楽しむこともできます。

¹: [YouTubeはフェイクニュースをどうやって排除するのか？](^1^)

²: [Netflixはなぜ韓国ドラマに力を入れるのか？](^2^)

³: [Amazonプライム・ビデオとNetflixはどっちがおすすめ？ 料金や特徴を徹底比較](^3^)

: [TVer（ティーバ���）とは？使い方や見逃し配信期間などを徹底解説]

: [【2021】動画配信サービスおすすめ人気ランキング\u3000映画・アニメ・ドラマ見放題]

ソース: Bing との会話 2023/8/16

(1) Amazonプライム・ビデオとNetflixはどっちがおすすめ？ 料金や .... https://mag.app-liv.jp/archive/132693/

(2) AmazonプライムビデオとNetflixを徹底比較、選ぶならどっち .... https://appllio.com/amazon-prime-video-vs-netflix

(3) 結局どこがいいの？NetFlixからAmazon Primeまで「動画配信 .... https://precious.jp/articles/-/19283

(4) 結局どこがいいの？NetFlixからAmazon Primeまで「動画配信 .... https://precious.jp/articles/-/19283

(5) Amazonプライム・ビデオとNetflixはどっちがおすすめ？ 料金や .... https://mag.app-liv.jp/archive/132693/

(6) AmazonプライムビデオとNetflixを徹底比較、選ぶならどっち .... https://appllio.com/amazon-prime-video-vs-netflix

上記回答用プロンプト

Netflix・Amazonプライムなどと、YouTubeやTVerなどの無課金動画だけ見ることのメリット・デメリット・情報源の質や偏りを解説して。

[calliopeservices2]

AI Reputation Manager : Le Nouveau Métier pour Référencer Votre Entreprise sur les Plateformes IA

L’intelligence artificielle (IA) transforme notre façon de communiquer, d’interagir et même de gérer la réputation des entreprises. Aujourd’hui, un nouveau métier émerge : l’AI Reputation Manager. Ce professionnel est spécialisé dans l’optimisation de la présence et de la réputation d’une entreprise sur les plateformes alimentées par l’IA. Ce rôle s’inscrit désormais dans l’offre de Communication & Marketing Digital de Calliope Services, qui accompagne les entreprises dans leur transformation digitale.

L’intelligence artificielle (IA) transforme notre façon de communiquer, d’interagir et même de gérer la réputation des entreprises. Aujourd’hui, un nouveau métier émerge : l’AI Reputation Manager. Ce professionnel est spécialisé dans l’optimisation de la présence et de la réputation d’une entreprise sur les plateformes alimentées par l’IA. Ce rôle s’inscrit désormais dans l’offre de Communication…

[intelvueofficial]

ChatGPT Invention 😀😀

ChatGPT is not new, Courage the Cowardly Dog was the first who use ChatGPT 😀😀😀😀

[pilog-group]

Future of AI 2025: Key AI Predictions for 2025 by Dr. Imad Syed | PiLog Group

Artificial Intelligence (AI) is rapidly transforming every sector, from healthcare to manufacturing, finance, and beyond. As we look ahead to 2025, the integration of AI into business and everyday life is set to redefine innovation and productivity.

In a recent insightful video, Dr. Imad Syed, a renowned thought leader and digital transformation expert, shares his predictions about the future of AI in 2025 and what businesses must prepare for.

Watch Dr. Imad Syed’s Predictions on AI 2025 Here:

Key Insights on the Future of AI by Dr. Imad Syed

AI and Human Collaboration: AI will not replace humans but enhance their capabilities, enabling smarter decision-making and better productivity.

2. Personalized AI Experiences: From customer service to healthcare, AI will offer hyper-personalized experiences tailored to individual needs.

3. Ethics and AI Governance: With AI becoming deeply integrated into society, ethical considerations and governance frameworks will play a critical role.

4. AI in Cybersecurity: AI will become central in predicting, preventing, and managing cybersecurity threats.

5. AI in Business Automation: Industries will leverage AI-driven automation to streamline operations and reduce costs.

Why You Should Care About These Predictions?

Understanding the future of AI is not just for tech enthusiasts — it’s a strategic advantage for business leaders, entrepreneurs, and decision-makers. Dr. Imad Syed’s insights provide a roadmap for adapting and thriving in a world powered by AI.

If you’re in technology, business management, or innovation strategy, this video is a must-watch.

Gain Exclusive Insights Now: Future of AI 2025 — Dr. Imad Syed

Global Impact of AI by 2025

By 2025, AI will: 1. Create smarter supply chains and logistics. 2. Revolutionize healthcare with predictive diagnostics. 3. Improve environmental sustainability through smart energy solutions. 4. Drive unparalleled innovation in financial services.

The future is AI-driven, and staying informed about these trends is the key to leading, not following.

Final Thoughts: Prepare for an AI-Powered Future

Dr. Imad Syed’s predictions are not just forecasts — they are action points for businesses and individuals who want to stay ahead of the curve.

Don’t miss this chance to gain valuable insights from a global leader in AI and digital transformation.

Watch Now: Future of AI 2025 — Dr. Imad Syed

Let us know your thoughts and predictions in the comments below. Are you ready for the AI revolution?