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Analyticsindiamag
1w
303
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Collaborations Shape Real-World AI Solutions in 2024
- AI collaborations played a big part in 2024, with businesses and governments partnering to solve complex challenges.
- High-profile collaborations and investments among big tech companies, like AWS and Anthropic, resulted in further innovation in the field of AI.
- Collaboration allows for faster and more efficient expansion of AI across sectors, as seen through the partnerships between Wayfair, Google, and OpenAI in e-commerce, and IBM and NTT Data in finance.
- Beyond traditional tech giants, countries like India are emerging as strong players with partnerships like the launch of India’s largest AI supercomputer with Telangana government and Yotta.
- Collaborations supporting AI growth in developing countries like India will democratise access to resources, increasing global competition further.
- Collaborations between OpenAI and media outlets, such as Time magazine, demonstrate the growing role of AI in content generation.
- Integrating AI in highly regulated industries requires more innovative solutions. Collaborations like the partnership between T-Mobile and OpenAI show a move towards transformative intelligent agents that comprehend and interoperate with humans.
- The establishment of centres of excellence in AI by MSDE and Meta highlights India’s rapidly growing role in AI on both domestic and global stages.
- Effective partnerships help address AI’s main challenges, including automation, data privacy and security.
- Collaboration is the future of AI, not just to make it smarter, but also to solve real-world challenges like improving healthcare and tackling climate change.
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Medium
1w
132
Image Credit: Medium
Computer Vision 01: Demystifying CNNs: A Beginner’s Guide to Computer Vision
- A CNN typically consists of the following layers: Max-Pooling, Average-pooling, Convolution layer, Fully Connected layer.
- The output shape of a convolutional layer depends on the input shape, filter size, stride, and padding.
- The number of parameters in a layer is determined by the number of filters, filter size, and the number of input channels.
- CNNs have revolutionized the field of computer vision, enabling a wide range of applications.
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Analyticsindiamag
1w
746
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Eureka Robotics Secures $10.5 Mn Series A Funding to Advance AI Deployment
- Singapore-based start-up Eureka Robotics has raised $10.5 million in a Series A funding round led by B Capital.
- The funding will be used to advance the development of Eureka Robotics' flagship products, the Eureka Controller and Eureka 3D Camera.
- The company aims to automate repetitive and hazardous tasks in manufacturing and logistics, allowing human workers to focus on creative work.
- Eureka Robotics plans to scale operations in Singapore and Japan, and enter the US market with its AI and robotics technology.
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Medium
1w
402
Image Credit: Medium
Ameca: The Humanoid with Emotions(?)
- Ameca by Engineered Arts is a humanoid robot designed to engage people in a human-like way.
- Its lifelike facial expressions and gestures are made to feel natural and relatable, offering a glimpse into the future of human-robot interaction.
- Ameca is equipped with advanced AI and hardware that not only makes it look like a human but also enables it to recognize emotions and actions of humans.
- Its gestures, like nodding, waving, and tilting its head, mimic how humans communicate through body language.
- Ameca’s modular design allows for easy replacement and upgrade of its parts with new technology as it becomes available.
- Ameca can be used across various industries for multiple applications, including education, healthcare, and customer service.
- Ameca’s emotional intelligence creates trust between humans and robots, which is a crucial aspect of human-robot relationships.
- As humanoid robots like Ameca evolve, ethical questions regarding their integration into our lives need to be addressed responsibly and ethically.
- Ameca’s ability to mimic human expressions and interact naturally opens up exciting possibilities for the future, but we must approach these technologies with responsibility and foresight.
- Individuals have a crucial role to play in advancing ethical AI and robotics for a future where technology serves humanity with respect and purpose.
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Analyticsindiamag
1w
1.2k
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Infosys Partners with RheinEnergie to Advance Energy Transition for Enterprises
- Infosys collaborates with RheinEnergie to support enterprises in their energy transition and sustainability goals.
- The partnership focuses on leveraging cloud technology, AI, and Industry 4.0 to improve energy efficiency and decentralize energy transition.
- Enterprises can select low-carbon energy sources, optimize investments, and benefit from renewable energy systems.
- The collaboration aligns with Germany's energy strategy and targets sectors like travel, transportation, commercial real estate, and manufacturing.
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Medium
1w
376
Image Credit: Medium
10 Essential Python Hacks for AI Developers to Boost Efficiency
- Python is a powerful programming language widely used in AI development.
- This article highlights 10 Python features that can boost efficiency in AI projects.
- One of the featured Python features is the built-in decorator that caches the results of expensive function calls.
- Using caching can speed up training time in AI projects.
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Medium
1w
329
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Late Deliveries and Ratings: Propensity Score Matching Approach
- Late delivery impacts customer satisfaction, an important metric for e-commerce platforms like Olist which connects small businesses across Brazil to channels for product delivery. Late deliveries are inevitable at times, fortunately, with causal inference and Propensity Score Matching (PSM), businesses can conduct observational studies to see the impact of late deliveries on customer ratings.
- PSM is used to reduce estimation bias when conducting evaluations with observational data. Propensity scores are the likelihood of an observation being exposed to treatment; late delivery status in this case.
- The likelihood of an order being late is based on a logistic regression analysis of certain order characteristics, giving it a propensity score. Late and on-time deliveries are matched by their similarity in propensity scores to create balanced groups.
- The objective of matching late deliveries to on-time deliveries is to measure the causal effect of late delivery on customer rating. Based on the resulting -1.97 average treatment effect of late delivery on the matched sample, we can conclude that late deliveries decrease customer satisfaction significantly.
- This analysis shows that customer satisfaction is reduced significantly due to late delivery. Platform developers should critically investigate better solutions and logistics models to ensure prompt order delivery in order to maximize customer satisfaction.
- A waiting time minimization model could be developed, which minimizes the wait time for each order, taking into consideration parameter like order size, time window in which the order was placed, and distance to customer’s delivery address.
- Another option would be to invest in real-time route optimization software, which would optimize delivery routes for each logistics partner with many supporting features. This would increase the number of deliveries a single logistics partner could handle in a day while ensuring timely delivery of orders.
- In conclusion, businesses must look beyond product quality and focus on ensuring timely delivery of customer orders. Delays in delivery are detrimental to customer satisfaction. The use of causal inference and PSM makes observational studies possible for businesses to identify factors that hinder customer satisfaction and to develop strategies that reduce them, including logistics improvements.
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Mit
1w
184
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Teaching a robot its limits, to complete open-ended tasks safely
- Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory used a combination of vision models and large language models (LLMs) to train robots to execute open-ended tasks safely and efficiently, ensuring machines deal with uncertainties and constraints. Their trial-and-error method, Planning for Robots via Code for Continuous Constraint Satisfaction (PRoC3S), creates a simulation on-the-fly of what’s around the robot and tests long-horizon plans to ensure they satisfy all constraints, until it arrives at one that can be executed. In simulations, PRoC3S successfully executed diverse tasks such as drawing, writing, and block placement, while also applying the approach to real-world tasks on robotic arms and table surfaces.
- The MIT researchers aim to use more scalable data-search techniques and applicable to mobile robots such as a quadruped for tasks that include walking and scanning surroundings. PRoC3S could provide assistance in public care centers and other areas requiring human-robot collaboration. The research team was supported, in part, by the National Science Foundation, the Air Force Office of Scientific Research, the Office of Naval Research, the Army Research Office, MIT Quest for Intelligence, and The AI Institute.
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Mit
1w
287
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AI in health should be regulated, but don’t forget about the algorithms, researchers say
- Researchers from MIT and Boston University are calling for more oversight of AI in healthcare.
- They argue that regulatory bodies should regulate AI algorithms in addition to AI itself.
- The U.S. Office for Civil Rights issued a new rule under the Affordable Care Act prohibiting discrimination in patient care decision support tools.
- Researchers also highlight the importance of regulating non-AI clinical decision support tools to ensure transparency and nondiscrimination.
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Medium
1w
38
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The Future of Artificial Intelligence: What Does ChatGPT Predict for 2030?
- Artificial intelligence (AI) has emerged as a cornerstone of technological innovation, driving transformative changes across industries such as healthcare, transportation, education, and manufacturing.
- The 2020s have been pivotal in the history of AI, fueled by significant breakthroughs in computational power, data availability, and algorithmic sophistication.
- Breakthroughs in Language Models: The introduction of large-scale language models such as GPT-3 and GPT-4 showcased AI’s near-human capabilities in understanding and generating text.
- Advances in Computer Vision and Speech Recognition: AI’s journey also included remarkable strides in computer vision and speech recognition.
- AI Democratization: During this period, AI became more accessible to developers and organizations through open-source frameworks like TensorFlow, PyTorch, and Hugging Face.
- The convergence of big data and AI has been instrumental in the rapid evolution of intelligent systems.
- Data as the Driving Force: Big data acts as the lifeblood of AI, providing the raw material necessary for training complex models.
- Advances in Data Storage and Processing: The rise of cloud computing and distributed databases has enabled organizations to store and process massive datasets efficiently.
- Autonomous systems are anticipated to dominate transportation, logistics, and urban mobility, revolutionizing the way goods and people move.
- Natural Language Processing (NLP) technologies are set to achieve unprecedented capabilities, bridging communication gaps and enabling context-aware interactions.
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Analyticsindiamag
2w
330
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OpenAI introduces Santa Mode to do what o1 Couldn’t
- OpenAI announced video and screen-sharing capabilities in ChatGPT's advanced voice mode.
- Users can engage in real-time visual and audio interactions with ChatGPT.
- Santa Mode introduced in ChatGPT allows users to interact with Santa in real-time.
- OpenAI's innovation reflects a broader vision of making AI interactions richer and more human-like.
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VentureBeat
2w
171
Lambda launches ‘inference-as-a-service’ API claiming lowest costs in AI industry
- Lambda, a San Francisco-based company, has launched the Lambda Inference API, which claims to be the lowest-cost service of its kind on the market.
- The API allows enterprises to deploy AI models and applications into production for end-users without worrying about procuring or maintaining compute.
- Lambda's Inference API supports leading-edge models and offers pricing starting at $0.02 per million tokens.
- The API targets a wide range of users, from startups to large enterprises, in media, entertainment, and software development.
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Medium
2w
128
Image Credit: Medium
Revolutionizing Industries with Generative AI: Unlocking New Creative Horizons
- Generative AI tools like ChatGPT and Jasper AI are transforming marketing, media and entertainment industries by generating engaging articles, social media posts, and visual assets quickly and efficiently.
- Generative AI is also revolutionizing the healthcare industry by accelerating drug discovery and optimizing patient care. AlphaFold predicts protein structures, while AI-driven platforms design personalized treatment plans based on patient data.
- In the gaming industry, Generative AI enables game developers to generate complex characters, immersive environments, and dynamic narratives at scale, making interactive gaming more accessible and engaging for players.
- Generative AI tools like Khan Academy’s Khanmigo provide tailored tutoring based on individual learning styles and progress, making learning more personalized and accessible.
- AI is redefining the fields of architecture and urban planning by enabling the design of optimized, sustainable structures. Generative AI tools like Autodesk’s Dreamcatcher explore multiple design configurations based on constraints like material costs, energy efficiency, and user needs.
- Generative AI enhances creativity by automating routine tasks, freeing up time for human creators to focus on more strategic and innovative aspects of their work, reducing costs and allowing for more personalized and engaging customer experiences.
- According to Forbes, generative AI is transforming content creation in marketing and media by enabling more dynamic and targeted communication strategies that drive engagement and conversions.
- Generative AI in healthcare enables faster and more cost-effective drug development, reducing the time from research to market, and improves patient outcomes with AI-powered diagnostics and personalized healthcare.
- AI tools in the gaming and entertainment industry enable game developers to build more personalized and dynamic gaming environments, making interactive gaming more accessible and engaging for players.
- Generative AI makes learning more individualized and accessible, by providing customized learning experiences that adapt to individual needs, making learning more engaging and effective.
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Towards Data Science
2w
49
Image Credit: Towards Data Science
CV VideoPlayer — Once and For All
- CV VideoPlayer is an open-source Python-based video player package designed for computer vision practitioners.
- It allows for interactive rendering of videos and frames with customizable overlays and frame edits.
- Custom visualizations can be added using the frame_edit_callbacks argument.
- CV VideoPlayer also supports keyboard shortcuts for enabling/disabling and changing visualizations.
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VentureBeat
2w
145
Anthropic’s fastest model, Claude 3.5 Haiku, now generally available
- Anthropic has made its Claude 3.5 Haiku model generally available through the Claude chatbot on web and mobile apps.
- Claude 3.5 Haiku outperforms larger models on benchmarks and offers competitive pricing.
- The model has a lower latency but slower output speed compared to average.
- Claude 3.5 Haiku excels in real-time tasks and features a 200,000-token context window.
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