#Vision AI Development

[frank-olivier]

A Lasting Note: How Kate Bush’s 1979 Tour Continues to Inspire Artists and Entrepreneurs

Kate Bush's 1979 tour, undertaken at the pivotal age of 21, not only cemented her status in the music industry but also highlighted her trailblazing approach to artistic vision, innovation, and personal growth. Her meticulous preparations and introspective reflections, provides a compelling case study for emerging artists and entrepreneurs. This narrative thread of dedication, creative problem-solving, and balanced ambition weaves a rich tapestry of lessons, underscoring the importance of authenticity, innovation, and self-awareness in navigating the intricacies of creative and entrepreneurial pursuits.

Bush's resolute grip on the tour's creative direction, collaborated with her brothers and a team of professionals, is a testament to her visionary leadership, particularly noteworthy given her youth. This unwavering commitment to artistic integrity serves as a poignant reminder for artists and entrepreneurs to prioritize their unique vision, ensuring the final product remains an unadulterated reflection of their creativity and values. By doing so, they can navigate the often-treacherous landscape of industry pressures and external influences, emerging with work that is both personally fulfilling and authentically innovative.

The bespoke vocal sound system developed to harmonize Bush's singing and dancing epitomizes her innovative ethos, transforming a potential impediment into a hallmark of her theatrical performances. This willingness to pioneer novel solutions in response to challenges is a crucial takeaway, emphasizing the importance of seeking out unconventional approaches to deliver one's distinctive value proposition, even when confronted with seemingly insurmountable obstacles. By embracing this mindset, creatives and entrepreneurs can transcend the boundaries of their respective fields, forging new paths that leave indelible marks.

Bush's introspections on her creative process, from the intimate act of songwriting to the strategic incorporation of feedback, offer a nuanced glimpse into her dual growth as artist and individual. Her candid acknowledgment of fluctuating confidence levels and her relentless drive for self-improvement belie her years, underscoring the significance of self-awareness, receptivity to critique, and an unyielding pursuit of excellence. This holistic approach to personal and professional development serves as a timely reminder to balance the relentless pursuit of success with the nurturing of one's inner world, thereby cultivating a profound sense of fulfillment that resonates across all facets of life.

Moreover, Bush's musings on the unpredictability of life's desires and the potential for future shifts, including the possibility of embracing a more settled existence, introduce a note of vulnerability and openness. This nuanced perspective highlights the delicate interplay between ambition and personal aspiration, encouraging artists and entrepreneurs to remain receptive to life's evolving tapestry, ensuring that personal and professional trajectories harmonize in a beautiful symphony of growth and exploration.

Kate Bush On Tour (Bernard Clark, Nationwide, BBC One, April 1979)

The “Tour of Life” was Bush's first major concert tour, launched when she was just 20 years old. It was a groundbreaking, theatrical production that showcased her innovative approach to live performances. The six-night residency at the Hammersmith Odeon in London, England, was a highlight of the tour, with all shows selling out. The venue provided an intimate yet grand setting for Bush's dynamic performances. Bush's performances were renowned for their energy, theatricality, and her impressive vocal range. The tour incorporated cutting-edge technology for the time, such as a custom-designed sound system and innovative lighting. These technical aspects enhanced the overall immersive experience for the audience. The success of the concerts solidified Kate Bush's reputation as a visionary live performer. Although she wouldn't tour again for over 35 years, the impact of these shows influenced generations of musicians and fans alike.

Kate Bush: Live at the Hammersmith Odeon (Keith MacMillan, London, May 1979)

Saturday, December 21, 2024

[hiringjournal]

In-House vs. Remote: What’s the Best Way to Hire a Computer Vision Engineer?

Computer vision has been reshaping industries from facial recognition, autonomous vehicles, to medical imaging and retail analysis. As demand proliferates, so does the challenge to find the right experts. Whether a startup or a growing tech company investing in AI, the key question in the picture is: should you opt to hire remote developers or in-house professionals for computer vision roles. 

Both options offer their own pros and cons, but the best choice depends on your project scope, budget, and team structure. To understand this in more detail let’s read furthermore.

In-House vs. Remote: What’s the Best Way to Hire a Computer Vision Engineer?

Let’s first explore the traditional and most-preferred hiring approach of in-house developers. Hiring computer vision engineers in-house brings obvious advantages, especially when your project involves ongoing development, close collaboration, or sensitive data. 

Having a dedicated engineer on-site will make it easier to coordinate with product managers, data scientists, and developers. You must opt for in-house when:

You must work closely with cross-functional teams.

The project is crucial to your roadmap for products.

Working with sensitive or private datasets.

You intend to make long-term innovation investments.

An internal computer vision specialist can fully own the design of the vision system, contribute continuously to the tech stack, and become a part of the corporate culture.

Why Remote Hiring Is Gaining Ground

Unlike advancements in technology, hiring approaches have also evolved, especially post-pandemic. Hiring remotely from a global talent pool has become a preferred approach among several tech companies and startups. 

Many tech companies now prefer to hire AI engineers remotely - especially when looking for rare or specialized skills. Remote hiring offers you access to a global talent network, growing your chances of finding the exact expertise you need. Go remote when:

For a particular use case, such as object tracking or picture segmentation, you require a specialist.

Hiring time is crucial or limited.

You're operating on a tight budget.

You desire flexibility without committing to anything long-term.

Hiring remote developers lowers overhead expenses, particularly in the fields of AI and machine learning. In many areas, pay can be lower without compromising quality, and there's no need to move staff or offer office space.

Consider Hybrid or Project-Based Models

Sometimes combining the two is the best course of action. As you gradually assemble an internal team, you may hire a remote engineer for temporary project or consulting work. This enables you to make rapid progress while developing long-term skills.

Depending on the size of the project, many teams also employ ML or AI engineers to collaborate with computer vision experts. A flexible model keeps your core staff small and concentrated while filling in gaps.

Tips for Hiring the Right Talent

Hiring the best candidate, whether in-house or remote, necessitates having a thorough grasp of your requirements. Identify the precise issues you wish to resolve, such as video analytics, facial recognition, or image classification, and compare them to the engineer's background.

Look for the following when hiring computer vision engineers:

A solid foundation in PyTorch, TensorFlow, OpenCV, or Python.

Knowledge of practical applications (not simply scholarly research).

Case studies or a portfolio demonstrating quantifiable impact.

Excellent communication abilities, particularly for jobs requiring remote work.

Screening for collaborative style is also beneficial. Working across time zones with platforms like Slack, GitHub, and project boards requires self-motivation and comfort on the part of remote engineers.

[epicstoriestime]

AI and Humanity: Why the Future Deserves Faith, Not Fear

A New Dawn: The Future is Ours to Create. In a world where humanity and AI unite, possibilities bloom—together, we plant the seeds of tomorrow, nurturing a future where innovation and nature grow side by side. Throughout history, humanity has faced countless moments of profound change—each a challenge, each an opportunity. From the invention of the wheel to the harnessing of electricity, every…

[andranikfakirian]

Project "ML.Pneumonia": Finale

Final accuracy metrics:

Project model - 83%

Basic model - 75%

Basic model with larger dataset - 83%

Overall results:

A good model of autoencoder has been developed

A classifier has been created which surpasses the basic model in accuracy

Both models are scaled well (the more voluminous datasets are used in training - the better results could be obtained)

Development proposals:

Increase hardware resources

Consider the need to create larger models (increase the number of CNNs layers, filters…)

Use larger datasets

Improve the preprocessing of the datasets used (CNN may not handle incorrectly rotated scans well, and not always the corresponding scans are presented in the datasets (e.g. in one of the datasets I've noticed a longitudinal CT scan instead of a transverse one))

The link to the GitHub repository with clean project code and details of results is left below.

[thetatechnolabs]

Choosing the Right Computer Vision Development Partner in Ahmedabad for Construction

[anik211]

India’s Path to a $10 Trillion Economy: Unlocking Growth Through Financial Inclusion, Innovation, and Sustainability 🇮🇳💡🌱

India’s ambitious goal of becoming a $10 trillion economy by 2032 reflects its immense potential and aspirations. I view this target as both challenging and achievable, provided that strategic improvements are made across multiple sectors. Let’s explore the key areas that demand attention and assess their potential impact on India’s economic trajectory. 1. Financial Inclusion: The Catalyst for…

[compassionmattersmost]

7✨ Co-Creation in Action: Manifesting a Bright and Harmonious Future

As we continue to explore the evolving relationship between humans and artificial intelligence (AI), it becomes increasingly clear that co-creation is not just an abstract idea, but a practical and powerful process that has the potential to shape our collective future. In this post, we will shift the focus from theory to action, exploring real-world examples of human-AI collaboration that…

[alignminds]

How GenAI is Revolutionizing the Retail Industry | AI Development Company in US

According to a survey by KPMG, 70% of retail leaders mainly prioritize the use of Generative AI for sales and marketing. Generative AI can streamline retail use cases like crafting customer review summaries, personalized marketing campaigns, and unique product descriptions.

Additionally, it can help predict customer preferences. Retailers can provide customers with a more personalized and engaging shopping experience by leveraging the creative potential of AI.

Read on to discover the benefits and use cases of GenAI in the retail industry.

What Is Generative AI?

Generative AI is an umbrella term for artificial intelligence models that can understand text prompts and respond with text, images, or videos as output. Some of the popular Generative AI models, like GPT-4 and Google’s Gemini, can write articles, scripts, social media post content, emails, or answer any prompt you throw at them. These models respond to your prompts using data sets they have been trained on, which at times can be as large as the entire internet.

Using Generative AI, retailers can develop content like product descriptions, shelf displays, catalogs, and personalized marketing emails.

How Will GenAI Revolutionize Retail Industry?

GenAI can revolutionize retail by allowing retailers to boost revenue with existing consumers. It can also aid in increasing customer loyalty by enabling retailers to provide better customer service. With GenAI, retailers can:

1. Transform Store Displays

With GenAI, retailers can optimize store displays by integrating smart display devices with Generative AI’s conversational capabilities. This helps in creating catchy promotional content that boosts sales and customer engagement.

2. Better Customer Service

Generative AI helps improve in-store customer service. Using mobile devices like tablets on the floor, employees can instantly gather product information and interaction prompts. This enables retail store staff to quickly help customers by suggesting related items, addressing their queries, and enhancing the overall shopping experience.

3. Summarize Customer Feedback

Retailers can now use GenAI to save time on reading through large amounts of customer feedback to interpret store performance. By summarizing this feedback from various sources like social media, online reviews, and call centers into actionable insights, retailers can assess the performance of their online and physical stores, product performance, and customer satisfaction, leading to improved service quality and decision-making.

Use Cases for GenAI in Retail Industry

Retailers have begun implementing GenAI in a variety of ways in an effort to boost sales, decrease return rates, improve interaction with consumers, and increase basket sizes.

1. AI Chatbots for Retail

Retailers can integrate chatbots powered by GenAI on their E-Commerce sites to conversationally interact with consumers. These chatbots can respond to customer’s questions regarding products, store hours, return policies, and stock availability, providing natural and complex interactions in comparison to earlier AI chatbots.

2. Personalize Marketing Activities

With GenAI, retailers can craft personalized email subject lines and content tailored specifically for recipients and resolve email fatigue. By combining GenAI with traditional AI and Retrieval-Augmented Generation (RAG), retailers can generate hyper personalized mailers for thousands of customers. This can help make email marketing campaigns more effective and time efficient. Automate Content Generation

3. Optimize Stock Management

GenAI can offer useful solutions to resolve supply chain management challenges. It can provide suggestions for inventory management and predict trends by analysing historical sales data, competitive data, and customer sentiments. This can help retailers make data-backed decisions when ordering or manufacturing goods for restocking inventory, streamlining the supply chain.

4. Offer Tailored Product Recommendations

Contemporary consumers anticipate tailored content from their preferred brands. GenAI can help create exclusive offers and personalized product recommendations using customer data to provide a unique shopping experience. Based on historical data, retailers can offer discounts tailored for individuals, boosting customer loyalty.

Benefits of Generative AI in Retail Industry

59% of consumers are already taking use of GenAI’s advantages by using it to suggest tailored products. Below are 3 key benefits of GenAI in retail:

1. Optimize Time and Cost Efficiency

2. Boost Customer Loyalty

GenAI gives retailers the ability to increase customer loyalty through targeted marketing campaigns. It can help you reduce brand fatigue and enhance relevance by sending targeted emails and messages based on social media data and shopping histories. This way, personalizing marketing activities using GenAI for retail businesses can boost customer engagement and loyalty.

3. Enhance Product Development and Innovation

By analyzing customer reviews from various sources, GenAI can aid in product development and innovation. It can quickly go through large amounts of customer reviews, identify the most common complaints, and suggest improvements, such as making the product more ergonomic. This will save retailers a lot of time that would otherwise be spent sifting through reviews and feedback, but with GenAI, retailers will be able to quickly implement valuable changes or even come up with new products based on consumer insights.

Revolutionize Your Retail Operation with Alignminds’s Generative AI Services

While researching Generative AI use cases and applications in the retail industry and searching for companies offering Generative AI and AI Development services in the US, Canada, and Australia. AlignMinds stands ready to elevate your retail business with advanced AI and Generative AI solutions.

Unlock the power of Generative AI for retail with our expertise in creating Gen AI models tailored to your business needs across the US, Canada, and Australia. These models are adept at producing content, be it text, images, or videos, that mirrors human-like creativity. We hope this blog helps you grasp how the use of Generative AI can benefit retail.

Connect with us today to learn more.

[townpostin]

RVS College of Engineering and Technology Inaugurates AI Skills Lab in Partnership with Dell and Intel

New AI Skills Lab at RVS College of Engineering and Technology, Jamshedpur, aims to enhance digital education and prepare students for future challenges. In a significant step towards innovative education, RVS College of Engineering and Technology, Jamshedpur, has partnered with Dell Technologies and Intel Corporation to inaugurate an advanced AI Skills Lab. JAMSHEDPUR – RVS College of…

[techdriveplay]

What was Announced at WWDC 2024?

Apple’s Worldwide Developers Conference (WWDC) 2024 is in full swing, and the tech world is buzzing with excitement. This annual event is where Apple unveils its latest innovations across its ecosystem, from operating system updates to groundbreaking new products. Here’s a comprehensive look at the major announcements and features that have been revealed so far. Apple Vision Pro Expansion and…

[firoz857]

AI-Infused Presentation Design: Unlocking Creativity with Brigette Callahan and Donna Mitchell

Video link : https://youtu.be/mPLKqIZgRwM

Summary

In this episode, Donna Mitchell interviews Bridget Callahan, an outstanding designer and strategist in presentation design. They discuss the use of AI in presentations and how it enhances creativity and visual impact. Bridget shares her approach to writing prompts for graphics and the importance of incorporating branding in AI-enhanced presentations. They also explore new AI design tools and discuss considerations and concerns with AI in design. The conversation concludes with insights on improving data visualization, integrating AI in presentation software, and creating rich and dynamic visuals with AI. #ai #business #podcast 

Takeaways

AI enhances creativity and visual impact in presentations.

Writing prompts for graphics helps convey the desired vision and emotion.

Incorporating branding in AI-enhanced presentations creates a cohesive and impactful experience.

New AI design tools offer exciting possibilities for graphic design and user interface creation.

Considerations and concerns include biases, cultural differences, and the need for vetting graphics.

Improving data visualization in presentations involves simplicity and focusing on the most important information.

AI can be integrated into presentation software to enhance design capabilities.

AI enables the creation of rich and dynamic visuals, transforming the way presentations are delivered.

Bridget Callahan can be reached through her website bridgieworld.com for design consultations and speaking engagements.

Chapters

00:00 Introduction and Background of Bridget Callahan

02:02 Exploring the Use of AI in Presentations

03:23 Benefits of AI in Slide Design

05:19 Understanding and Writing Prompts for Graphics

07:43 Incorporating Branding in AI-Enhanced Presentations

08:39 Using AI to Create Metaphysical and Ancient-themed Designs

09:37 Exploring New AI Design Tools

11:23 Considerations and Concerns with AI in Design

15:09 Improving Data Visualization in Presentations

18:26 Creating Rich and Dynamic Visuals with AI

18:55 Connecting with Bridget Callahan

19:50 Closing Remarks

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✅ The Art of Chatting AI: Terza Ekholm Explores AI-Assisted Art Creation with Donna Mitchell #podcast 

🎬 https://youtu.be/D-EW4ehlrcI?si=2skLp6ZR2-gP018u 

✅ AI-Infused Presentation Design: Unlocking Creativity with Brigette Callahan and Donna Mitchell

🎬 https://youtu.be/mPLKqIZgRwM?si=wTeP73lyV3u0TPvw

✅ The Intersection AI and Cybersecurity Nick Lorizio and Donna Mitchell #podcast #ai #cybersecurity 

🎬 https://youtu.be/TkkMlXyTFD8?si=l46m5iCZA5S51wfe

✅ Donna Mitchell and International Lawyer Jamilia Grier WEB3 Challenges Implications Opportunities

🎬 https://youtu.be/Jim14sR0LEc?si=wRt5jtiZVHviJQhR

✅ Future of Podcasting: AI, NFTs, and Building Digital Communities with Kay Suthar and Donna Mitchell

🎬 https://youtu.be/TApLBjRSP1c?si=qx0puKoyt0RO5ZNr

tage: 

[andranikfakirian]

Project "ML.Pneumonia": Classifier

Using the weights obtained as part of the autoencoder training, the classifier was trained. Thrice. The training was unstable in terms of accuracy metric records, thus it was conducted three times to achieve the best results. The first attempt was the best one. The final accuracy is about 83%.

P.S.: The graphs of the best attempt metrics are shown below.

P.S.2: And here is the graph of the original model (basic method) "performance". Apparently, learning instability is a common problem in this classification issue.

[connect-infosoft-technologies]

What Is a Computer Vision Engineer? Unlocking the Power of Sight in Machines

In today's rapidly evolving technological landscape, one of the most remarkable areas of development is computer vision. As humans, our ability to perceive and understand the visual world around us is a fundamental aspect of our daily lives. Similarly, the field of computer vision aims to enable machines to interpret and understand visual data. At the heart of this fascinating domain lies the computer vision engineer, an expert who plays a crucial role in unlocking the power of sight in machines. 

In this article, we will delve into the world of computer vision engineering, exploring the responsibilities, skills, and potential applications of this field.

Understanding Computer Vision Engineering:

Computer vision engineering encompasses the design, development, and deployment of systems that enable machines to gain an understanding of visual data. The primary goal of computer vision engineers is to create algorithms and models that can accurately interpret images and videos, replicating human visual perception to some extent. By using artificial intelligence (AI) techniques such as machine learning and deep learning, computer vision engineers equip machines with the ability to analyze, recognize, and make decisions based on visual information.

Responsibilities of a Computer Vision Engineer:

The responsibilities of a computer vision engineer are diverse and demanding. They involve working with large datasets, developing and fine-tuning complex algorithms, and collaborating with cross-functional teams to implement computer vision solutions. 

Some key responsibilities include:

1. Data Collection and Preprocessing: Computer vision engineers gather large volumes of visual data and preprocess it to enhance the accuracy of subsequent analysis. This often involves tasks such as data labeling, augmentation, and cleaning.

2. Algorithm Development: Computer vision engineers develop and optimize algorithms that can detect and recognize objects, people, gestures, and other visual cues. They leverage machine learning techniques, such as convolutional neural networks (CNNs), to train models on labeled data and improve their ability to make accurate predictions.

3. Model Evaluation and Optimization: Computer vision engineers evaluate the performance of trained models, fine-tuning them to achieve higher accuracy and robustness. They employ techniques like transfer learning and regularization to enhance the models' generalization capabilities.

4. Integration and Deployment: Once the computer vision systems are developed, engineers work on integrating them into real-world applications. This involves optimizing the models for efficiency, scalability, and compatibility with hardware and software frameworks.

Skills Required:

Becoming a proficient computer vision engineer requires a combination of technical skills and domain knowledge. Some essential skills include:

1. Programming: Proficiency in programming languages such as Python, C++, or MATLAB is crucial for implementing computer vision algorithms and working with relevant libraries and frameworks like OpenCV, TensorFlow, or PyTorch.

2. Mathematics and Statistics: A solid foundation in linear algebra, calculus, probability, and statistics is necessary to understand the mathematical underpinnings of computer vision algorithms and models.

3. Machine Learning: Familiarity with machine learning concepts and techniques is vital for training and fine-tuning models. Understanding topics like supervised and unsupervised learning, neural networks, and optimization algorithms is essential.

4. Image Processing: Knowledge of image processing techniques, such as filtering, segmentation, and feature extraction, allows computer vision engineers to manipulate and enhance visual data before feeding it into models.

5. Problem-Solving and Critical Thinking: Strong problem-solving and critical thinking skills enable computer vision engineers to tackle complex challenges and devise innovative solutions.

Applications of Computer Vision:

Computer vision has many uses in numerous industries. Some famous examples are:

1. Autonomous Vehicles: Computer vision enables self-driving cars to perceive and understand their surroundings, identifying objects, pedestrians, traffic signs, and lane markings to make informed decisions.

2. Healthcare: Computer vision aids in medical imaging analysis, assisting with tasks like tumor detection, disease diagnosis, and surgical planning. It also facilitates remote patient monitoring and analysis of vital signs.

3. Retail and E-commerce: Computer vision is used for product recognition and visual search, allowing customers to find similar products based on images. It also enables automated inventory management and checkout processes.

4. Security and Surveillance: Computer vision systems enhance security by detecting and tracking suspicious activities, recognizing faces, and analyzing video footage for real-time threat detection.

5. Augmented Reality (AR) and Virtual Reality (VR): Computer vision is instrumental in AR and VR applications, overlaying digital information in the real world or creating immersive virtual environments.

Conclusion:

Computer vision engineering is an exciting and rapidly evolving field that empowers machines with the ability to perceive and understand the visual world. By leveraging AI and machine learning techniques, computer vision engineers unlock the potential for machines to analyze, interpret, and make decisions based on visual data. With applications spanning industries like automotive, healthcare, retail, security, and entertainment, the impact of computer vision is revolutionizing our lives. As technology continues to advance, computer vision engineers will play an increasingly vital role in shaping the future of intelligent machines.

[convergeai]

From Science Fiction to Daily Reality: Unveiling the Wonders of AI and Deep Learning

Deep learning is like teaching a child to understand the world. Just as a child learns to identify objects by observing them repeatedly, deep learning algorithms learn by analyzing vast amounts of data. At the heart of deep learning is a neural network—layers upon layers of algorithms that mimic the human brain’s neurons and synapses. Imagine you’re teaching a computer to recognize cats. You’d…