ChatGpt-Bard-Comprehensive-Comparision

ChatGPT vs. Bard: A Comprehensive Comparision

Introduction

Both ChatGPT and Bard are advanced language models developed by OpenAI, aiming to excel in natural language understanding and generation tasks. In this comparison, we'll delve into their differences across several key dimensions.

Model Architecture

ChatGPT: Based on the GPT-3.5 architecture, ChatGPT is a powerful language model with 175 billion parameters, capable of generating coherent and contextually relevant text.

Bard: Utilizing a novel architecture, Bard introduces advancements beyond GPT-3.5, potentially featuring improvements in handling context, coherence, and understanding user inputs.

Text Generation Quality

One of the primary benchmarks for language models is the quality of generated text.

Coherence and Contextual Understanding

ChatGPT: Excels in maintaining context and generating coherent responses, but may sometimes produce responses that lack deep understanding of specific queries.

Bard: Aims to improve upon contextual understanding, providing more nuanced and contextually relevant responses. The architecture might be designed to enhance coherence and reduce instances of generating nonsensical or irrelevant text.

Creativity and Originality

ChatGPT: Known for its creative outputs, capable of generating unique and contextually appropriate content.

Bard: Expected to surpass ChatGPT in terms of creativity, potentially introducing novel ways of expressing ideas and generating original content.

Fine-Tuning and Customization

Fine-tuning capabilities allow users to tailor the model to specific tasks or domains.

Adaptability

ChatGPT: Offers fine-tuning capabilities, allowing users to adapt the model to various applications, although some challenges exist in achieving precise control over outputs.

Bard: May introduce advancements in fine-tuning capabilities, enabling users to achieve more precise control and customization, catering to a broader range of specialized applications.

Domain-Specific Performance

ChatGPT: Performs reasonably well in domain-specific tasks with fine-tuning but may exhibit limitations in highly specialized contexts.

Bard: Expected to show improvements in domain-specific performance, potentially outperforming ChatGPT in tasks that demand a deep understanding of specific domains.

Handling Ambiguity and Vagueness

Both models are evaluated in their ability to handle ambiguous or vague queries.

Ambiguity Resolution

ChatGPT: Demonstrates a moderate ability to resolve ambiguity but may struggle with highly ambiguous queries.

Bard: Aims to improve ambiguity resolution, leveraging advancements in its architecture to provide clearer and more precise responses to ambiguous inputs.

Vagueness Handling

ChatGPT: Sometimes produces vague responses when faced with unclear queries, requiring additional prompts for clarification.

Bard: Expected to exhibit enhanced vagueness handling, potentially reducing the need for repeated prompts and providing more accurate responses in ambiguous scenarios.

Ethical Considerations and Bias Mitigation

Addressing ethical concerns and mitigating biases in language models is crucial for responsible AI development.

Bias Mitigation

ChatGPT: Faces challenges in completely eliminating biases and may inadvertently generate biased content.

Bard: Aims to incorporate improved mechanisms for bias detection and mitigation, contributing to a more ethical and unbiased language generation.

Ethical Use Cases

ChatGPT: Encourages ethical use but requires users to be mindful of potential misuse and ethical considerations.

Bard: May introduce enhanced ethical guidelines and features to discourage misuse, promoting responsible and ethical use of the model.

User Interaction and Interface

The user experience and interaction with the models play a vital role in their practical utility.

Responsiveness

ChatGPT: Generally provides prompt and responsive interactions, with minimal latency in generating responses.

Bard: Aims to maintain or improve responsiveness, ensuring a seamless and efficient user experience.

User-Friendly Interface

ChatGPT: Interacts through a user-friendly text-based interface, accessible to a wide range of users.

Bard: Expected to retain or enhance user-friendliness, with potential improvements in understanding user inputs and providing more user-centric interactions.

Table: Summary of Differences

Aspect Open AI ChatGPT Google Bard
Model Architecture GPT-3.5 Novel architecture (beyond GPT-3.5)
Text Generation Quality Coherent, contextually relevant Improved coherence, deeper understanding
Fine-Tuning and Customization Fine-tuning capabilities Advanced fine-tuning with improved customization
Handling Ambiguity and Vagueness Moderate ambiguity resolution Enhanced ambiguity resolution, reduced vagueness
Ethical Considerations and Bias Mitigation Challenges in bias mitigation Improved bias detection and mitigation
User Interaction and Interface Responsive and user-friendly Maintained or improved responsiveness and interface
Pricing ChatGPT 3.5 is free for users. But , ChatGPT, GPT 4, is a paid subscription for $20/month. Free for all as of now.
Developer OpenAI Alphabet/Google
Image generation Cannot generate images Can generate images
Internet access No Yes

 

How Bard and ChatGPT Boost Speed and Efficiency in Different Work Domains:

ChatGPT

  1. Content Summarization:

Application: ChatGPT's proficiency in summarizing text makes it invaluable for automating content summarization tasks. It can be applied in fields such as journalism, research, and content curation, where quick and accurate summarization of lengthy texts is crucial for efficiency.

  1. Drafting and Writing Assistance:

Application: ChatGPT's text generation capabilities make it a valuable tool for drafting content efficiently. It can be employed in writing emails, reports, or articles, streamlining the content creation process.

  1. Code Generation and Review:

Application: In software development, ChatGPT can be used to generate code snippets and assist in code reviews. This application can significantly accelerate the coding process and improve code quality.

  1. Customer Support Automation:

Application: ChatGPT can be integrated into customer support systems to handle routine queries, providing quick and accurate responses. This speeds up customer interactions and allows human agents to focus on more complex issues.

Bard:

  1. Real-time Information Retrieval:

Application: Bard's strength in providing up-to-date information makes it ideal for applications requiring real-time data. This includes fields such as news reporting, financial analysis, and data-driven decision-making.

  1. Conversational Interfaces:

Application: Bard's architecture is well-suited for creating conversational interfaces in applications like chatbots. This can enhance the efficiency of customer service, virtual assistants, and other interactive platforms.

  1. Medical Information and Research:

Application: In the medical field, Bard can be utilized to stay current with the latest research and advancements. This is crucial for healthcare professionals who need quick access to relevant information for diagnosis and treatment.

  1. Education and Training:

Application: Bard's conversational abilities can be harnessed for educational purposes, providing interactive and engaging learning experiences. It can be applied in virtual classrooms, training simulations, and e-learning platforms to improve learning efficiency.

Comparative Analysis Bard and ChatGPT:

Overlap in Content Creation: Both models can contribute to content creation, but ChatGPT's strength lies in generating and summarizing textual content, while Bard focuses on real-time information and conversational interfaces.

Complementary Use Cases: ChatGPT and Bard can be complementary in certain scenarios. For example, ChatGPT can be used to draft content, and Bard can be integrated for fact-checking or adding the latest information.

Task Complexity: ChatGPT may excel in tasks requiring a deep understanding of context, while Bard's efficiency shines in tasks that demand real-time updates and interactive conversations.

Key Takeaways

ChatGPT and Google Bard stand out as formidable AI chatbots, each showcasing unique strengths in content generation. While ChatGPT distinguishes itself with its exceptional ability to summarize text, Bard takes the lead in providing accurate and current information when responding to questions. This divergence in expertise is rooted in their respective underlying architectures—ChatGPT harnesses the power of GPT-3.5, whereas Bard relies on Google's innovative LaMDA model.

ChatGPT's forte lies in its proficiency in condensing information into concise and coherent summaries. Leveraging the GPT-3.5 architecture, ChatGPT excels in processing and distilling textual content, making it particularly adept at tasks that demand a comprehensive understanding of the input data and the ability to present it succinctly.

On the other hand, Bard, powered by Google's LaMDA, takes center stage in the realm of conversational AI. Its specialization in providing responses with the latest information positions it as an ideal choice for users seeking real-time and up-to-date knowledge. The LaMDA architecture, designed by Google, enhances Bard's conversational capabilities, allowing it to excel in delivering timely and contextually relevant answers to user queries.

The contrasting strengths of these AI chatbots make them complementary tools, catering to distinct use cases. ChatGPT's prowess in text-based processing is well-suited for applications requiring in-depth understanding and summarization of content. Meanwhile, Bard's proficiency in conversational tasks makes it an invaluable resource for users seeking immediate and precise information.

ChatGPT and Google Bard emerge as powerful AI chatbots, each carving its niche in content generation. Whether prioritizing summarization or real-time information retrieval, users can leverage these platforms strategically based on their specific requirements.

Google-Gemini

The Google Gemini Era is Here!

Yesterday Sundar Pichai tweeted and introduced  Gemini 1.0 and mentioned it as Google’s  most capable and general AI model yet.

Demis Hassabiss, CEO and Co-Founder of Google DeepMind also tweeted and introduced Gemini 1.0.

What is Gemini from Google?

Gemini is built from the ground up for multimodality — reasoning seamlessly across text, images, video, audio, and code. Google Gemini is multimodal and first one in the Gemini-era of models. It is the one of the most popular methods to test the knowledge and problem solving abilities of AI models. Gemini is optimized in three sizes - Ultra, Pro, and Nano. Pichai added, Ultra’s performance exceeds current state-of-the-art results on 30 of the 32 widely-used academic benchmarks. With a score of 90.0%, Gemini Ultra is the first model to outperform human experts on MMLU.

Gemini 1.0  is optimized in three sizes

  • Gemini Ultra— Google’s largest and most capable model for highly complex tasks.
  • Gemini Pro— Google’s best model for scaling across a wide range of tasks.
  • Gemini Nano— Google’s most efficient model for on-device tasks.

What is MMLU?

MMLU (Massive Multitask Language Understanding) is a new benchmark designed to measure knowledge acquired during pretraining by evaluating models exclusively in zero-shot and few-shot settings. This makes the benchmark more challenging and more similar to how we evaluate humans. The benchmark covers 57 subjects across STEM, the humanities, the social sciences, and more. It ranges in difficulty from an elementary level to an advanced professional level, and it tests both world knowledge and problem solving ability. Subjects range from traditional areas, such as mathematics and history, to more specialized areas like law and ethics. The granularity and breadth of the subjects makes the benchmark ideal for identifying a model’s blind spots.

What can Gemini do?

Google Gemini can help in the following problem solving scenarios:

  1. It Excels at competitive programming
  2. It Unlocks insights in scientific literature
  3. It can Process and understand raw audio signal end-to-end
  4. It can explain and help understand in math and physics
  5. It can reason about the user intent to generate bespoke experiences

On the Google technology blog Demis added Its remarkable ability to extract insights from hundreds of thousands of documents through reading, filtering and understanding information will help deliver new breakthroughs at digital speeds in many fields from science to finance.

Demis also added that Gemini was combined with robust filters, this layered approach is designed to make Gemini safer and more inclusive for everyone. Additionally, we’re continuing to address known challenges for models such as factuality, grounding, attribution and corroboration. It will surely will enhance creativity, extend knowledge, advance science and transform the way billions of people live and work around the world.

With these kind of features it can be helpful to coders, businesses, students, teachers and parents.

Google also announced that they have incorporated Gemini Pro in Bard for new ways to collaborate with AI. Gemini Ultra will come to Bard early next year in a new experience called Bard Advanced.

What is Bard?

Bard is Google's experimental, conversational, AI chat service. It is meant to function similarly to ChatGPT, with the biggest difference being that Google's service will pull its information from the web.

Bard has a share conversation function and a double check function that helps users fact-check generated results. Bard can also access information from a number of Google apps and services, including YouTube, Maps, Hotels, Flights, Gmail, Docs and Drive, letting users apply Bard to their personal content.

Let's roll back to late November 30, 2022, when ChatGPT was released. Less than a week after launching, ChatGPT had more than one million users. According to analysis by Swiss bank UBS, ChatGPT became the fastest-growing 'app' of all time. Other tech companies, including Google, saw this success and wanted a piece of the action.

In the same week that Google unveiled Bard in February, 2023, Microsoft unveiled a new AI-improved Bing, which runs on a next-generation OpenAI LLM customized specifically for search.

ChatGPT was released on November 30, 2022. In just under a week post-launch, ChatGPT amassed over one million users, escalating to the status of the fastest-growing 'app' in history, according to an analysis conducted by the Swiss bank UBS. The success of ChatGPT caught the attention of various tech giants, Google among them, all eager to partake in this burgeoning phenomenon.

In a parallel move during the same week in February 2023, Google unveiled Bard. Simultaneously, Microsoft introduced an upgraded version of Bing powered by AI advancements. This new Bing iteration utilized a cutting-edge OpenAI LLM specifically tailored for enhanced search functionality.

Google Gemini Availability

  • Google Gemini is now available on Pixel 8 Pro and Bard
  • It will be accessible to developers and enterprise users from December 13.
  • Gemini Ultra is still under evaluation and will be released for wide usage next year.

The AI game has just begun but it is for sure that it is here to stay.

This video below highlights some interactions with Gemini.

Learn more and try the “multimodal prompting” model on the link below:

https://developers.googleblog.com/2023/12/how-its-made-gemini-multimodal-prompting.html 

 

AI-Emerging-Jobs

Emerging Job Opportunities In The Era Of Growing AI Adoption

As we find ourselves in the final month of 2023, one undeniable trend that has characterized this year is the remarkable surge in the utilization of artificial intelligence (AI). It is very evident that AI has not merely been a passing trend but has, instead, solidified its presence as a transformative force in our lives.

This technological shift is more than just a fleeting development; it is reshaping our very identities and altering the manner in which we connect with and perceive the world around us.

This  integration of AI proves that it is not merely a temporary phenomenon but is going  to play a pivotal role in shaping our future interactions and experiences.

With any emerging technological trends the first thing to get affected positively or adversely are the job descriptions and job titles. Everyone’s career sooner or later going to depend on how well you can use the AI tools for your efficiency, speed and productivity. The integration of AI into the workplace not only transforms the way tasks are executed but also reshapes the skill set and competencies that are crucial for professional success.

The future of AI in digital marketing is expected to be transformative, bringing about significant changes and opportunities. As AI continues to advance, it is essential for professionals in digital marketing to stay updated on emerging technologies and acquire the necessary skills to adapt to the evolving landscape. Continuous learning and a proactive approach to embracing AI can open up exciting career opportunities in the field of digital marketing.

While I don't have real-time information on specific job titles and descriptions for emerging careers in 2024, I am sharing some  general trends and areas where new job opportunities are likely to emerge as a result of advancements in AI and related technologies.

Keeping in mind that the field is rapidly evolving, and the specifics may vary.  Here are some trends and potential emerging careers in the intersection of AI and digital marketing:

  • Prompt Engineer
  • AI Trainer/Teacher
  • AI Governance and Ethics Specialists
  • AI-driven Content Creator
  • AI SEO Specialist
  • AI Marketing Compliance Manager
  • AI Security Analyst
  • AI Marketing Strategist
  • Social Media AI Analyst
  • AI Integration Specialist

Let’s  explore and seek to uncover and comprehend the dynamic shifts in the professional sphere, highlighting the emerging avenues that hold significant potential for individuals seeking new and promising career paths.

  1. Prompt Engineer

Well-crafted prompts play a pivotal role in enabling the AI model to grasp the user's intention and context, ultimately resulting in responses that are both accurate and pertinent.

A prompt is a text that goes into the AI tool - Language Model (LM), and prompt engineering is the art of designing that text to derive the desired output. It involves tailoring input that is clear and concise, which helps AI-powered tools understand the user’s intent. Hence, to effectively use this process, it is essential to ensure that AI-powered tools don’t generate nonsensical, inappropriate responses.

Hence, the efficiency of the AI tool in use depends on how good you are in the way you prompt the AI. As the AI model may have all the answers but it can give you the best and the most relevant answer only if your prompt is framed the correct way.

Read more about prompt engineering on : https://www.techtarget.com/searchenterpriseai/definition/AI-prompt-engineer

  1. AI Trainer/Teacher

The AI trainer plays a key role in ensuring that AI functions at its best and provides a rewarding user experience. The AI trainer trains AI systems by creating datasets, defining algorithms, and optimizing models. This role involves understanding the nuances of human behavior to improve AI performance and user experience.

At the core of an AI Trainer’s role is the task of teaching chatbots how to think and interact. This isn’t as simple as just feeding data into a system. Yes, data is crucial, but the real skill lies in carefully curating and shaping that data to train the AI effectively. It’s about understanding the subtleties of human conversation and teaching a chatbot to do the same. This is what transforms a complex piece of code into a friendly, helpful assistant that can answer questions with ease.

Read More on : https://boost.ai/blog/ai-trainer-a-job-of-the-future/

  1. AI Governance and Ethics Specialists

The role of chief AI ethics officer (CAIEO) is on the rise at leading enterprises as digital transformation becomes more complex and AI adoption grows rapidly across industries.

Forward-looking companies are turning to the CAIEO role to put into operation corporate values related to AI across the organization's divisions.

CAIEOs need to ensure that the AI technology being developed, used and deployed is trustworthy; and that developers have the right tools, education, and training to easily embed these properties in what they produce.

CAIEOs should have multi-disciplinary knowledge of AI techniques, tools and platforms, AI risks and its impact on society, business strategy, industries and public policies, as well as good communication skills.

Simply put, the job involves ensuring the responsible and ethical development and deployment of AI technologies. This role involves creating guidelines and policies to address ethical concerns related to AI, such as bias, privacy, and transparency.

Read more on: https://www.weforum.org/agenda/2021/09/artificial-intelligence-ethics-new-jobs/

  1. AI-driven Content Creator

Creating compelling content involves several key elements, including topic selection, drafting, organization under sub-headings, proofreading, and tailoring language to specific geographic locations.

Each of these steps demands careful attention and considerable time investment. Moreover, staying updated with research, statistics, and opinions from thought leaders in the industry adds an additional layer of complexity.

As the content creator, one is  responsible for creating, reviewing and editing content for the company which will be published in the company's websites and social media pages. You will also be responsible for researching on the key SEO terms and implementing them in the content to gain maximum exposure.

Developing content strategies that integrate AI-generated content. This involves using natural language processing (NLP) and content generation tools to create engaging and relevant content for digital marketing channels.

Read More on: https://www.webpro.in/ai-unleashed-navigating-the-future-of-seo-content-creation-with-chatgpt/

  1. AI SEO Specialist

Every SEO know the importance of keeping abreast with the latest algorithm updates and how they affect the search results. An AI SEO Specialist has to add another dimension and also know how the search engines are incorporating AI in the search algorithms.

Just came across a job description for AI SEO Specialist on: https://www.naukri.com/job-listings-b2b-ai-seo-specialist-dg7-mumbai-3-to-8-years-260823501467

It goes as follows:

Job description

The AI SEO Specialist will be responsible for developing and implementing AI-powered SEO strategies to improve the organic search visibility and ranking of our website. This role will require a deep understanding of SEO principles and practices, as well as the ability to use AI tools and techniques to automate and scale SEO tasks.

Key Responsibilities :

The ideal candidate for the B2B AI SEO Specialist role should possess the following skill set:

  • Machine Learning Algorithms: Proficiency in understanding and applying various machine learning algorithms, such as regression, clustering, classification, and recommendation systems, to enhance SEO strategies.
  • AI-Enhanced Content Creation: Experience with AI-powered content generation tools that can assist in creating high-quality, relevant, and optimized content for improved search rankings.
  • Predictive Analytics: Ability to leverage predictive analytics models to anticipate changes in search engine algorithms and user behavior, allowing for proactive adjustments to SEO strategies.
  • Image and Video SEO: Familiarity with AI techniques for optimizing images and videos, including image recognition, alt text optimization, and video transcription, to improve multimedia search visibility.
  • Voice Search Optimization: Understanding of AI-driven voice search technology and its implications for SEO, including optimizing for voice-based queries and featured snippets.
  • Natural Language Generation (NLG): Proficiency in NLG tools to create AI-generated content that resonates with both search engines and human readers, maintaining a natural tone and relevance.
  • A/B Testing with AI: Experience in conducting A/B tests using AI-powered tools to compare different SEO strategies and identify the most effective ones based on real-time data.
  • Chatbots and Virtual Assistants: Knowledge of AI-powered chatbots and virtual assistants and their role in enhancing user engagement, answering queries, and improving overall website experience.
  • Data Visualization and Reporting: Skill in using AI-driven data visualization tools to present complex SEO insights in a clear and visually appealing manner to stakeholders.
  • Sustainable AI Strategy: Ability to implement AI SEO strategies that align with long-term sustainability and ethical considerations, ensuring compliance with search engine guidelines.
  • Semantic Search Optimization: Understanding of semantic search concepts and utilizing AI to improve content s semantic relevance and context for search engines.
  • Local SEO with AI: Familiarity with AI applications for local search optimization, including geo-tagging, local intent optimization, and enhancing local business listings.
  • Algorithmic Penalty Recovery: Experience in using AI-driven data analysis to identify and recover from algorithmic penalties, and adapting strategies to maintain compliance.
  • AI-driven Link Building: Knowledge of AI tools that can assist in identifying authoritative and relevant link-building opportunities, enhancing the website s backlink profile.
  • Social Media AI Integration: Ability to integrate AI-enhanced content into social media strategies for cross-channel optimization and improved audience engagement.
  • Continuous Learning: Enthusiasm for staying updated with the latest advancements in both AI and SEO fields, attending conferences, webinars, and online courses as necessary.
  • AI-Driven Strategy: Develop and execute innovative SEO strategies that incorporate AI and machine learning techniques to optimize website content, structure, and user experience.
  • Keyword Research: Utilize AI tools to identify relevant keywords and search trends, and integrate them strategically into website content for improved organic search rankings.
  • Content Optimization: Collaborate with content creators to implement AI-driven content recommendations, including keyword integration, semantic analysis, and topic relevance.
  • Technical SEO: Work closely with developers to ensure proper implementation of technical SEO aspects, such as site speed optimization, mobile responsiveness, schema markup, and AI-generated metadata.
  • Data Analysis: Leverage AI-powered analytics tools to monitor and analyze website performance, organic traffic trends, and user behavior, providing actionable insights for continuous improvement.
  • Competitor Analysis: Utilize AI tools to analyze competitors SEO strategies, identifying opportunities for differentiation and improvement.
  • Algorithm Updates: Stay up-to-date with search engine algorithm changes and trends in AI and machine learning in the SEO landscape, adapting strategies as needed.
  • Natural Language Processing (NLP): Apply NLP techniques to enhance on-page SEO elements, including meta descriptions, headers, and other content components.
  • Collaboration: Work cross-functionally with content creators, developers, designers, and other teams to implement AI SEO strategies effectively.

By possessing these additional AI-driven skills, the AI SEO Specialist will be well-equipped to navigate the ever-evolving landscape of search engine optimization, leveraging artificial intelligence to stay ahead of the curve and deliver exceptional results.

Skills:

  • Bachelor s degree in Marketing, Computer Science, Data Science, or a related field. Master s degree preferred.
  • Proven experience (3+ years) in SEO, with a focus on AI and machine learning integration.
  • Proficiency in using AI tools and platforms for SEO, such as AI-generated content tools, NLP libraries, and predictive analytics tools.
  • Strong understanding of search engine algorithms, ranking factors, and SEO best practices.
  • Familiarity with programming languages like Python, as well as AI frameworks and libraries.
  • Excellent analytical skills and the ability to interpret data trends and user behavior.
  • Up-to-date knowledge of industry trends and algorithm updates.
  • Outstanding communication and collaboration skills.
  • Certifications in AI, machine learning, and SEO are a plus.

 

Reading the above description I am sure everyone is convinced that SEO is not only more technical today but requires  experience, expertise and specific skill to do justice to the job.

  1. AI Marketing Compliance Manager

 The main task of an AI Marketing Compliance Manager is to ensuring that AI-driven marketing strategies comply with legal and ethical standards. This role involves staying updated on privacy regulations, data protection laws, and industry guidelines to mitigate risks associated with AI in marketing.

The larger perspective of AI compliance is also to assure that AI-powered systems are employed responsibly and in a way that benefits society.

Not being able to use AI in a way that is fully compliant with the applicable law may result in high fines and penalties.

To ensure full AI compliance, organizations should take into account the following best practices:

  1. Establish clear policies and procedures for AI use.
  2. Develop a comprehensive compliance program.
  3. Monitor AI systems for compliance with applicable laws and regulations.
  4. Create an AI governance framework.
  5. Ensure data privacy and security.
  6. Establish an audit process for AI systems.
  7. Develop a process for reporting and responding to compliance issues.
  8. Implement a risk management program.
  9. Train personnel on AI compliance requirements.
  10. Utilize automated tools to monitor AI compliance.

Read more on: https://www.exin.com/article/ai-compliance-what-it-is-and-why-you-should-care/

  1. AI Security Analyst

This job involves Protecting AI systems from cyber threats and ensuring the security of data used in AI models. This role involves staying updated on the latest cybersecurity trends and developing strategies to mitigate risks

To understand better, read the job description here: https://www.ziprecruiter.in/jobs/289817241-ai-cyber-security-penetration-testing-specialist-at-sap-successfactors

  1. AI Marketing Strategist

This position entails the creation and implementation of AI-driven marketing strategies. It involves harnessing AI algorithms to scrutinize market trends, consumer behavior, and competitor strategies, with the aim of optimizing marketing campaigns for maximum impact.

AI marketing strategy integrates artificial intelligence technologies and methodologies to refine and elevate marketing endeavors. It entails employing AI to analyze customer data, streamline processes, tailor experiences, and enhance decision-making, ultimately fostering improved marketing outcomes.

The role of an AI Marketing Strategist encompasses the development and execution of marketing strategies heavily reliant on AI technologies. These professionals bear the responsibility of identifying opportunities where AI can augment marketing efforts, such as optimizing ad campaigns and automating customer segmentation.

AI plays a pivotal role by conducting predictive analytics on customer data, swiftly analyzing vast datasets using efficient machine learning (ML) algorithms. It not only generates insights about future customer behavior but also recommends more personalized content and identifies patterns within extensive datasets for marketers to act upon.

AI Marketing Strategists serve as a bridge between technology and marketing, contributing to the realization of superior results. Their expertise lies in seamlessly integrating advanced technology into marketing initiatives to drive enhanced performance and outcomes.

Content on  https://www.salesforce.com/ap/resources/guides/role-of-ai-in-marketing/ can be helpful reading on this topic.

  1. Social Media AI Analyst

A Social Media Analyst is a professional who specializes in analyzing and interpreting data from various social media platforms to provide valuable insights and recommendations for businesses or individuals. The role involves monitoring social media channels, collecting data, and using analytics tools to understand the performance of social media campaigns, audience engagement, and overall social media presence.

Some of the tasks that a Social Media AI Analyst is responsible for:

  • Integrating artificial intelligence tools and technologies into social media analysis processes to enhance efficiency, automate tasks, and derive deeper insights.
  • Leveraging AI algorithms for advanced data analytics to analyze large volumes of social media data. This could include sentiment analysis, trend prediction, and pattern recognition to extract meaningful insights.
  • Developing and implementing systems that use AI to automate the process of generating social media analysis reports. This can save time and ensure real-time or near-real-time reporting.
  • Applying predictive analytics powered by AI to forecast the success of social media campaigns. This could involve predicting engagement rates, click-through rates, and other key metrics before launching a campaign.
  • Utilizing AI algorithms for more sophisticated audience segmentation on social media platforms. This involves identifying and categorizing users based on their behavior, preferences, and demographics.
  • Overseeing the performance and impact of content generated by AI, such as automated posts, comments, or responses. Ensuring that AI-generated content aligns with brand guidelines and resonates with the target audience.

Read more on: https://www.marketingaiinstitute.com/blog/what-is-artificial-intelligence-for-social-media

 

     10. AI Integration Specialist

In this role, you will be responsible for the integration of AI technology across the entire organization and the maintenance of AI and new technologies to support the organization's efforts to stay at the forefront of the advertising industry.

The responsibilities can be listed as follows:

  • Develop and implement a comprehensive AI integration plan across all departments of the agency, including web & graphics, video production, photography, and digital.
  • Research and evaluate new AI tools and technologies that could support the specific use cases in each department.
  • Test and evaluate AI tools in their intended use cases to ensure that they can effectively support the department's workflow.
  • Create process documentation and training resources for the use of AI tools across the organization.
  • Train employees on the use of AI tools and process documentation to ensure their effective integration into daily workflows.
  • Monitor and evaluate the impact of AI on the specified use cases in each department to identify areas for improvement.
  • Keep abreast of new developments in AI technology and recommend updates and improvements as necessary.
  • Collaborate with the management team to develop and implement strategies to leverage AI technology to improve performance, reduce costs and increase efficiency.
  • Create an “Evidence of Improvement” by project type, department, and use case to track benefits of AI implementation.
  • Troubleshoot and debug AI systems and resolve any integration issues
  • Continuously monitor the performance of AI-powered systems, looking for ways to optimize and improve them.
  • Implement automation between tools and applied technologies.
  • Act as a liaison between the technical and non-technical teams, helping to communicate AI needs, plans and developments.

As you can see that the emerging job opportunities and the evolving job landscape due to the increasing use of the AI tools is not only promising but interesting too.

Implementation of AI is not taking jobs away, it is only eliminating routine and repetitive tasks, making way for more stimulating and complex responsibilities.

18-09-2019

Google Updates its Rules for Review Rich Search Results

18-09-2019 Google posted on the webmaster blog today that  they have updated the review rich  rules for how and when it shows the reviews rich results. Search results that are enhanced by review rich results can be extremely helpful when searching for products or services (the scores and/or “stars” you sometimes see alongside search results). Google said that to make the review rich results more helpful and meaningful, they are now introducing algorithmic updates to reviews in rich results. review rich search results The main takeaway from this is that if the functionality of posting the reviews on the site is such that they can be moderated or updated then they will not be shown. This applies to even the reviews posted via the third party widgets.

With this change, Google has also  limited the pool of schema types that can potentially trigger review rich results in search. Specifically, they will only display reviews with those types (and their respective subtypes):

According to Google:

Reviews that can be perceived as “self-serving” aren't in the best interest of users. We call reviews “self-serving” when a review about entity A is placed on the website of entity A - either directly in their markup or via an embedded 3rd party widget. That’s why, with this change, we’re not going to display review rich results anymore for the schema types LocalBusiness and Organization (and their subtypes) in cases when the entity being reviewed controls the reviews themselves.

search-console-team

Google Bids Farewell To The Old Search Console

The search console is a vital and a valuable tool for the SEOs. No SEO can neglect the data offered in this tool.

As of May 20, 2015, Google rebranded Google Webmaster Tools as Google Search Console.In January 2018, Google introduced a new version of the Search Console, with a refreshed user interface and improvements.

 
Google search-console-team

Google launched the new Search Console at the beginning of 2019. Since then Google has been upgrading the new search console and also responding to the  feedback sent by the webmasters.

Google has reached another important milestone and has bid a farewell to many old Search Console reports, including the home and dashboard pages.

dashboard-Google-search-console

The old search console which was known as Webmaster Tools prior to 2015 helped site owners and webmasters to monitor and improve their performance on Google Search for over a decade.

Google says:

"From now on, if you try to access the old homepage or dashboard you’ll be redirected to the relevant Search Console pages. There are only a few reports that will still be available on the old interface for now - check the Legacy tools and reports in the Help Center. We're continuing to work on making the insights from these reports available in the new Search Console, so stay tuned!"

Google Search Console

If you want to share any Search Console memories or stories, please use the hashtag #SCmemories  on Twitter.

General changes

The new Search Console has the following improvements over the old version:

  • Sixteen months of search traffic data, versus three months in the old product
  • Detailed information about a specific page, including index coverage, canonical URL, mobile usability, and more
  • Tracking flows to help you monitor, fix, and request a recrawl of pages affected by crawling issues.
  • New and improved reports and tools, described next.
  • Works on mobile devices.

Currently unsupported features by the new Search Console:

Here are some features that aren't yet supported in new Search Console. To use them you will have to use the old Search Console, for now.

  • Crawl Stats data (pages crawled per day, KB downloaded per day, page download times)
  • Robots.txt tester
  • Managing URL parameters in Google Search
  • Data highlighter tool
  • Reading and managing your messages
  • Change of address tool
  • Setting preferred domain
  • Associating your Search Console property with an Analytics property
  • Disavow links
  • Removing outdated content from the index

GDPR - General Data Protection Regulation : 20 Key Points

  1. GDPR stands for General Data Protection Regulation.
  2. Its purpose is to unify all EU member states' approaches to data regulation, so that all data protection laws are applied identically in every country within the EU.
  3. It will protect EU citizens from organisations using their data irresponsibly.
  4. It ensures that EU citizens are in charge of the information which is shared about them.
  5. It also gives them the charge to know where and how it's shared.
  6. The GDPR will come into force on 25 May - and even though the UK is due to leave Europe in the next 12 months, it will still apply to all businesses handling EU residents' data, effectively replacing the Data Protection Act 1998.
  7. Any business found not complying  to the rules could be charged fines of up to €20 million or 4% of the company's global annual turnover.
  8. The toughest fines will be reserved for the worst data breaches or data abuse.
  9. GDPR is a regulation, not a directive, the UK does not need to draw up new legislation - instead, it will apply automatically.
  10. 'Controllers' and 'Processors' of data need to abide by the GDPR.
  11. Even if controllers and processors are based outside the EU, the GDPR will still apply to them so long as they're dealing with data belonging to EU residents.
  12. All types of data organizations who collect about people, online identifiers such as IP addresses now qualify as personal data.
  13. Other data, like economic, cultural or mental health information, are also considered personally identifiable information.
  14. Pseudonymised personal data may also be subject to GDPR rules, depending on how easy or hard it is to identify whose data it is.
  15. People have the right to access any information a company holds on them.
  16. People have the right to know why that data is being processed, how long it's stored for, and who gets to see it.
  17. Read More on Rules for the protection of personal data inside and outside the EU on https://ec.europa.eu/info/law/law-topic/data-protection_en
  18. Read More On GDPR Fines on http://www.itpro.co.uk/general-data-protection-regulation-gdpr/31025/gdpr-fines-how-high-are-they-and-how-can-you-avoid
  19. GDPR Compliance Checklist on https://gdprchecklist.io/
  20. Questions to Consider in order to assess if you are GDPR ready - https://www.hubspot.com/data-privacy/gdpr-checklist

 

Walmart Buys 77% stake In FlipKart - Amazon in talks to buy Stake In Future Retail

On May 9th 2018  Walmart announced that,

Walmart will pay approximately $16 billion for an initial stake of approximately 77 percent in Flipkart.

The remainder of the business will be held by some of Flipkart’s existing shareholders, including Flipkart co-founder Binny Bansal, Tencent Holdings Limited, Tiger Global Management LLC and Microsoft Corp.

While the immediate focus will be on serving customers and growing the business, Walmart will support Flipkart’s ambition to transition into a publicly-listed, majority-owned subsidiary in the future.

About FlipKart:

Founded in 2007, Flipkart has led India’s eCommerce revolution. The company has grown rapidly and earned customer trust, leveraging a powerful technology foundation, including artificial intelligence, and emerging as a leader in electronics, large appliances, mobile and fashion and apparel.

In 2015 FlipKart had adopted an App only strategy and had shut down their website. But, they found it difficult to provide an efficient user experience and soon shifted to a website which combined the benefits of the App and website and called their Progressive Web App as FlipKart Lite.

The FlipKart  PWA  resulted in :

  • 3X more time spent on site
  • 40% higher re-engagement rate
  • 70% greater conversion rate among those arriving via Add to Homescreen
  • 3X lower data usage.

Some Major Commercial Reasons Walmart shared in their Investor Presentation are:

  1. "India is one of the most attractive retail markets in the world, given its size and growth rate, and our investment is an opportunity to partner with the company that is leading transformation of e-commerce in the market," Walmart CEO Doug McMillon said in a statement.
  2. Flipkart has 54 million active consumers, and with this influx of money it can double this base in short period of time.
  3. Walmart commits to sustained job creation and investment in India which is one of the largest and fastest-growing economies in the world.
  4. Flipkart’s supply chain arm, eKart, serves more than 800 cities, making 500,000 deliveries daily.
  5. “Flipkart has established itself as a prominent player with a strong, entrepreneurial leadership team that is a good cultural fit with Walmart,” said Judith McKenna, president and chief executive officer of Walmart International.
  6. Over the last 10 years, Flipkart has become a market leader by focusing on customer service, technology, supply chain and a broad assortment of products.
  7. Walmart’s investment includes $2 billion of new equity funding, which will help Flipkart accelerate growth in the future.
  8. While Walmart and Flipkart will leverage the combined strengths of both companies, they will maintain distinct brands and operating structures.

Indian e Commerce Market

The FlipKart – Walmart deal surely scales a major success graph for the Indian eCommerce start-up but, it also passes on the control of the online retail business in India to two large American companies – Walmart and Amazon.

Soon after this announcement Amazon is said to be in talks with India’s largest brick-and-mortar retail company Future Retail, to acquire a stake.

Future Retail  is the retail arm of Kishore Biyani.  Future Group, owns physical retail stores such as Big Bazaar and Easy Day.

“Future has consolidated the market. There are only three big retailers left: Reliance Retail, D-Mart and Future Retail… Future is an attractive target,” said Abneesh Roy, senior vice-president (research) at ‎Edelweiss Capital.

Roy added that Future and Amazon can be of use to each other. For example, Future Retail can learn from Amazon’s global sourcing business. On the other hand, Amazon in India can take the help of Future’s supply chain. Future Group has a fully-owned subsidiary called Future Supply Chain Solutions. It has a network of 46 distribution centres, which includes four temperature-controlled centres — spread out in a ‘hubs and branches’ model, covering 11,228 PIN codes.

 

Dr_Vint_Cerf_ForMemRS-200x300

Vint Cerf and Robert Kahn – The Men Who developed TCP/IP Receive A Franklin Institute Award.

Google’s Chief Internet Evangelist Vint Cerf and Robert Kahn have been awarded a Franklin Institute Award for developing TCP/IP, the protocol that allows effective communication between millions of computer networks.

About Franklin Institute Award:

Since 1824, The Franklin Institute of Philadelphia has honored the legacy of Benjamin Franklin by presenting awards for outstanding achievements in science, engineering, and industry. Past laureates include Thomas Edison, Marie Curie, Claude Shannon, Jane Goodall, Nikola Tesla, Stephen Hawking, Edward Lorenz, the Wright Brothers, Bill Gates, and Albert Einstein.

What Is TCP/IP?

TCP/IP technically applies to network communications where the TCP transport is used to deliver data across IP networks. A so-called "connection-oriented" protocol, TCP works by establishing a virtual connection between two devices via a series of request and reply messages sent across the physical network.

Who Is Vint Cerf?

  1. Vinton Gray Cerf is an American Internet pioneer, who is recognized as one of "the fathers of the Internet"
  2. In the early days, Cerf was a manager for the United States' Defense Advanced Research Projects Agency(DARPA) funding various groups to develop TCP/IP technology.
  3. Cerf was instrumental in the funding and formation of ICANN from the start.
  4. Cerf is active in many organizations that are working to help the Internet deliver humanitarian value to the world. He is supportive of innovative projects that are experimenting with new approaches to global problems, including the digital divide, the gender gap, and the changing nature of jobs.
  5. Cerf is also known for his formal attire, typically appearing in a three-piece suit daily for work—a rarity in an industry known for its casual dress norms.

Who is Robert Kahn?

  1. After receiving a B.E.E. degree in electrical engineering from the City College of New York in 1960, Kahn went on to Princeton University where he earned a M.A. in 1962 and Ph.D. in 1964.
  2. In 1972, he began work at the Information Processing Techniques Office (IPTO) within Defense Advanced Research Projects Agency(DARPA).
  3. In the fall of 1972, he demonstrated the ARPANET by connecting 20 different computers at the International Computer Communication Conference.
  4. He then helped develop the TCP/IP protocols for connecting diverse computer networks.
  5. He started the United States government's billion dollar Strategic Computing Initiative, the largest computer research and development program ever undertaken by the U.S. federal government.
  6. After thirteen years with DARPA, he left to found the Corporation for National Research Initiatives (CNRI) in 1986, and as of 2015 is the chairman, CEO and president.

7 Ways Big Data Is Changing The Way Marketers Reach Their Audience

At the focal point of modern marketing is information. Without quality information, you cannot know how to get convertible leads. However, today, marketing coincides with an interesting phase of innovation where big data plays a big role in how marketers go about their business. I will look at ways big data is shaping the way marketers reach their audience.

1. Makes Targeted Marketing Possible

Reaching to the market is an art that requires foolproof targeting. With analytics, you can scan the population for your market. Apart from feasibility tests of retails stores, which require analysis of target audience, even companies targeting global customers use the same level of targeting.

If you make products for Microsoft Windows users, you can reach directly to them using targeted ads and offers. You don't have to sell to everyone else who may not be interested blindly.

7 Ways Big Data Is Changing

2. Market Information Synergy To Understand The Customer

When it is about people as customers, the information about them is usually scattered across various media, authorities, and inherent in them. With analytics, you can bring together this information together and make sense of it. Companies today can target the customer with precision.

3. It Informs On The Marketing Message

With competent information about existing solutions, one can make the message right for the customer. To do this, you need to understand the frustrations, needs, and proposals that customers put across. For example, product updates are based on feedback, without it, the improvement would not matter.

4. Customer Engagement And Consequent Growth

Information is not just about the company to its customers. Internal information and reverse communication from customers to companies is very healthy. Companies leveraging on feedback achieve tremendous growth. According to research, companies that engage customers are growing faster than their counterparts that do not. Social media is a great way to communicate. After this exchange, making use of this information separates serious companies from pretenders.

5. Tailored Customer Products

Customers are increasingly interested in custom products. If it is an enterprise software, companies want it customized for their use. Knowing how many people who would be interested in your service, you can evaluate the economies of delivering the service. In the process, you can control a niche customer base unique only to you.

6. Budgeting Decisions About Market Channels

Being frugal in your marketing budget requires perfect information lest you affect the effectiveness of your campaign. With analytics, you can confidently identify media channels effective to your cause. Without this information, you are likely to gamble with your strategy, which is not good.

7. Being Where And When You Need The Product

It might come by surprise that you will receive emails about antivirus updates mostly on the third quarter of the year. Some types of promotional emails you only get them at the beginning of the year. Why is so? Companies use big data analytics to understand general trends, and they use them to know when to come to you.

Google-IO-2017

Google’s New Search Feature Connecting Job Seekers With employers

Google has announced “Google for Jobs” this year at Google I/O which is a brand new company-wide endeavor aimed at aiding both job seekers as well as employers through joint-effort with the job matching industry. One of the important aspects of this initiative is to provide job aspirants better exposure through Google Search Engine.

This new experience is open now for all developers and site owners. A job listings preview would be shown for queries with clear cut intent such as ‘head of catering jobs in nyc’ or ‘entry level jobs in DC’. Each job can be expanded for showing all-inclusive details regarding the listing.

This feature brings a host of benefits and adds a new dimension for employers and site owners with job content.

  • Prominent place in Search Results: The job postings can be displayed in the new job search feature on Google encompassing logo, reviews, ratings, and details of the job.
  • More, motivated applicants: Job filtering feature is present by different criteria which means it becomes easier to sort out applicants and candidates looking for the specific or exact job.
  • Increased chances of discovery and conversion: There would be a new vista open for job seekers to interact with employer's postings and click through to their site.

The job listings are available on Google whose implementation has got two steps:

  1. The job listings are to be marked up with Job Posting structured data.
  2. A sitemap (or an RSS or Atom feed) is to be submitted with a <lastmod> date for each listing.

If there are more than 100,000 job postings or more than 10,000 changes each day, one can make use of the High Change Rate feature.

If job openings are published already on other sites like LinkedIn, DirectEmployers, Monster, Glassdoor CareerBuilder and Facebook, they can still appear in the feature.

Making job search an embellished search experience Google has created a dedicated guide to help comprehend how Google ranking functions for enhanced search and practices for boosting the online presence.

Keeping track of doing and fixing issues

There are a handful of tools to facilitate the implementation:

  • Mark up can be validated with the Structure Data Testing Tool
  • Listing can be previewed in the Structured Data Testing Tool
  • In Search Console sitemap's status can be tracked.
  • In Search Console aggregate stats and markup error examples can be viewed.

Google would be adding new job listing filters in the weeks to follow in the Search Analytics report in Search Console so that one can track clicks and impressions for his/her listings.

 

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