Forwarded from پردازش داده ژنتیک و ژنومیک با هوش مصنوعی و یادگیری عمیق Genetic data analysis; Genomic data processing with AI and deep learning
مقاله ای بسیار مهم در ارتباط با روش crispr-cas9 با یادگیری عمیق و مدلهای LLMای مثل Chat-GPT (با تشکر از آقای زکی زاده)👇
Forwarded from پردازش داده ژنتیک و ژنومیک با هوش مصنوعی و یادگیری عمیق Genetic data analysis; Genomic data processing with AI and deep learning
bioRxiv
CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments
The introduction of genome engineering technology has transformed biomedical research, making it possible to make precise changes to genetic information. However, creating an efficient gene-editing system requires a deep understanding of CRISPR technology…
Forwarded from پردازش داده ژنتیک و ژنومیک با هوش مصنوعی و یادگیری عمیق Genetic data analysis; Genomic data processing with AI and deep learning
Researchers from Stanford University, Princeton University, and Google Deepmind have introduced CRISPR-GPT, a tool that merges CRISPR technology with advanced LLMs such as GPT-4. This integration facilitates the automation of gene-editing experiments, enabling precise genomic modifications with reduced complexity. The unique aspect of CRISPR-GPT lies in its ability to synthesize domain-specific knowledge with LLMs’ computational efficiency, streamlining the experimental design process in ways previously unachievable with general-purpose LLMs.
CRISPR-GPT employs a methodology integrating CRISPR technology with computational models based on LLMs, specifically GPT-4. The system utilizes a comprehensive dataset that includes CRISPR system efficiencies and guide RNA (gRNA) sequences, which are vital for optimizing the selection and design processes. The framework of CRISPR-GPT consists of multiple modules that automate tasks such as CRISPR system selection, gRNA design, and method delivery recommendations. Each module is powered by LLMs that have been fine-tuned with domain-specific biological data to ensure high accuracy and efficiency in gene-editing experiments.
CRISPR-GPT employs a methodology integrating CRISPR technology with computational models based on LLMs, specifically GPT-4. The system utilizes a comprehensive dataset that includes CRISPR system efficiencies and guide RNA (gRNA) sequences, which are vital for optimizing the selection and design processes. The framework of CRISPR-GPT consists of multiple modules that automate tasks such as CRISPR system selection, gRNA design, and method delivery recommendations. Each module is powered by LLMs that have been fine-tuned with domain-specific biological data to ensure high accuracy and efficiency in gene-editing experiments.
bioRxiv
CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments
The introduction of genome engineering technology has transformed biomedical research, making it possible to make precise changes to genetic information. However, creating an efficient gene-editing system requires a deep understanding of CRISPR technology…
Forwarded from Reza
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این نمایش بینظیر GPT-4o، یه پیشنمایش از آینده آموزشه. آیندهای که نیاز نیست شما برای یادگیری حتی از جاتون تکون بخورید چون در هرجا و هر لحظه، معلم در کنار شماست!
Forwarded from Reza
کانال یادگیری عمیق؛ کلان داده؛ هوش مصنوعی AI; Deep leaarning, Big data
این نمایش بینظیر GPT-4o، یه پیشنمایش از آینده آموزشه. آیندهای که نیاز نیست شما برای یادگیری حتی از جاتون تکون بخورید چون در هرجا و هر لحظه، معلم در کنار شماست!
This unique display of GPT-4o is a preview of the future of education. A future where you don't need to move even to learn because the teacher is by your side everywhere and at any time!
Channel name was changed to «کانال یادگیری عمیق؛ کلان داده؛ هوش مصنوعی AI; Deep leaarning, Big data»
هوش مصنوعی آنقدر مهم شد که یک کشور برایش وزیر تعیین کرد 👇
France appoints first AI minister amid political unrest as it aims to become global AI leader | Euronews
https://www.euronews.com/next/2024/09/23/france-appoints-first-ai-minister-amid-political-unrest-as-it-aims-to-become-global-ai-lea
https://www.euronews.com/next/2024/09/23/france-appoints-first-ai-minister-amid-political-unrest-as-it-aims-to-become-global-ai-lea
euronews
France appoints its first AI minister amid political unrest
Clara Chappaz, the former director of the La French Tech mission, will take up the role in Michel Barnier’s new cabinet.
یکی از سوالاتی که بعضا از بنده حقیر پرسیده می شود این است که اگر بخواهیم کسب و کار موفقی راه بیندازیم؛ در چه حوزه محصولی ای ورود کنیم. بنده اعتقاد دارم تفکر کسب و کار از همان روز اول باید بین المللی باشد و صادرات برای شرکتهای ایرانی در همین شرایط کنونی امری کاملا شدنی است و شرکتهای خوب همین الان دارند آنرا انجام می دهند. پیمان های پولی مثل BRICS هم که امکان کار با ارز سایر کشورها و مستقل از دلار و fatf هستند هم فرصتهای طلایی پیش روی کشور هستند. لذا شناخت بازار جهانی و بخصوص کشورهایی که رابطه خوبی با ما دارند مثل عراق؛ سوریه؛ لبنان؛ روسیه؛ هند؛ برزیل؛ ونزوئلا؛ یمن (از جهت مقصد صادراتی) بسیار مهم است. مطالعه ذیل که بر اساس مصاحبه با شرکتهای برتر صادراتی کشور و یا تحلیل بازار جهانی بر اساس اطلاعات سازمان جهانی توسعه تجارت می باشد؛ اطلاعات محصولات خوب جهت صادرات و مقاصد صادراتی را در اختیار شما قرار خواهد داد 👇
14-Software-&-Information-Technology---Fa---V5.pdf
47.7 MB
محصولات شرکتهای دانش بنیان با قابلیت صادرات در حوزه هوش مصنوعی؛ نرم افزار و فناوری اطلاعات
14-Software-&-Information-Technology---En---V5.pdf
47.4 MB
Artificial Intelligence, Software and Information technology Knowledge-based companies of Iran with export Capability
🔶 مایکروسافت هوش مصنوعی جدیدی برای تشخیص بیماریها ازجمله سرطان معرفی کرد
🔷 مایکروسافت هوش مصنوعی جدیدی را توسعه داده است که میتواند برای آنالیز تصاویر پزشکی کاربرد داشته باشد و برای مثال تومورها را پیدا کند. این مدل هوش مصنوعی براساس GPT-4 از OpenAI ساخته شده است.
🔷 ابزار هوش مصنوعی جدید این شرکت BiomedParse نام دارد. از این ابزار میتوان برای ارزیابی سیتیاسکن، امآرآی، تصاویر اشعه ایکس، اولتراسوند و انواع دیگر تصاویر پزشکی برای شناسایی مشکلات احتمالی یا تشخیص انواع سلولها یا سایر پدیدههای بیولوژیکی در یک تصویر استفاده کرد.
🔷 به گفته مایکروسافت، پزشکان برای استفاده از این ابزار لازم است ابتدا متنی را به آن بدهند؛ برای مثال، پزشکان میتوانند عبارت «سلولهای پاتولوژیک» را تایپ کنند و هوش مصنوعی محل قرارگرفتن آنها در تصویر را شناسایی میکند.
🗓تاریخ انتشار: Nov 18
📌منبع : Microsoft
#همراه_فاند #سرمایه_گذاری #مایکروسافت #پردازش_تصاویر_پزشکی
@hamrahfundcvc | hamrahfund.com
🔷 مایکروسافت هوش مصنوعی جدیدی را توسعه داده است که میتواند برای آنالیز تصاویر پزشکی کاربرد داشته باشد و برای مثال تومورها را پیدا کند. این مدل هوش مصنوعی براساس GPT-4 از OpenAI ساخته شده است.
🔷 ابزار هوش مصنوعی جدید این شرکت BiomedParse نام دارد. از این ابزار میتوان برای ارزیابی سیتیاسکن، امآرآی، تصاویر اشعه ایکس، اولتراسوند و انواع دیگر تصاویر پزشکی برای شناسایی مشکلات احتمالی یا تشخیص انواع سلولها یا سایر پدیدههای بیولوژیکی در یک تصویر استفاده کرد.
🔷 به گفته مایکروسافت، پزشکان برای استفاده از این ابزار لازم است ابتدا متنی را به آن بدهند؛ برای مثال، پزشکان میتوانند عبارت «سلولهای پاتولوژیک» را تایپ کنند و هوش مصنوعی محل قرارگرفتن آنها در تصویر را شناسایی میکند.
🗓تاریخ انتشار: Nov 18
📌منبع : Microsoft
#همراه_فاند #سرمایه_گذاری #مایکروسافت #پردازش_تصاویر_پزشکی
@hamrahfundcvc | hamrahfund.com
8 Companies Poised to Benefit Significantly from the AI Boom 👇
10 شرکتی که بیشترین بهره را از هوش مصنوعی برده اند 👇
8 Companies Poised to Benefit Significantly from the AI Boom - techovedas
https://techovedas.com/8-companies-poised-to-benefit-significantly-from-the-ai-boom/
https://techovedas.com/8-companies-poised-to-benefit-significantly-from-the-ai-boom/
techovedas
8 Companies Poised to Benefit Significantly from the AI Boom - techovedas
8 companies leading the AI boom and poised to capitalize on its immense potential.
8 companies leading the AI boom
1. Google (Alphabet Inc.):
Google’s dominance in the AI landscape stems from its extensive research and development efforts in machine learning, natural language processing, and computer vision.
Additionally,the company’s AI-powered products and services span a wide range of applications, from Google Search and Gmail to Google Photos and Google Maps.
Google’s open-source machine learning framework, TensorFlow, has become the industry standard for building and deploying AI models.
Moreover, Google’s acquisition of DeepMind Technologies has bolstered its AI capabilities, leading to breakthroughs in areas such as reinforcement learning and AlphaGo.
2. Amazon:
Amazon’s AI initiatives are integral to its core business operations, driving efficiency, personalization, and customer satisfaction.
The company’s AI-powered recommendation engine analyzes vast amounts of customer data to suggest products tailored to individual preferences, driving sales and enhancing user experience.
Additionally, Amazon’s investments in AI-driven logistics optimization have streamlined its supply chain operations, reducing costs and improving delivery times.
AWS offers a comprehensive suite of AI and machine learning services, including Amazon SageMaker, Amazon Recognition, and Amazon Comprehend, empowering businesses to harness the power of AI for their own applications.
8 Netflix Movies Redefining Artificial Intelligence – techovedas
3. Microsoft:
Microsoft’s AI strategy revolves around its Azure cloud platform, which provides a robust infrastructure for AI development and deployment.
Azure Machine Learning simplifies the process of building, training, and deploying AI models, while Azure Cognitive Services offers pre-trained AI models for vision, speech, language, and decision-making tasks.
Microsoft’s acquisition of LinkedIn has enabled the integration of AI-driven features into the professional networking platform, enhancing user engagement and productivity.
Additionally, Microsoft’s Project Brainwave initiative aims to accelerate AI workloads using specialized hardware, further solidifying its position in the AI space.
Read More: NVIDIA Crowns OpenAI King of AI with World’s First DGX H200 – techovedas
4. NVIDIA:
NVIDIA’s GPUs have become indispensable tools for AI researchers and developers, thanks to their unparalleled processing power and efficiency.
Additionally,the company’s CUDA programming platform and cuDNN library provide a robust framework for building and training deep learning models.
NVIDIA’s DGX system offers turnkey solutions for AI development and deployment, while the NVIDIA GPU Cloud provides a curated collection of AI software containers and workflows.
NVIDIA’s acquisition of Mellanox Technologies has strengthened its position in the AI infrastructure market, enabling high-speed data transfer and communication between GPU-accelerated systems.
1. Google (Alphabet Inc.):
Google’s dominance in the AI landscape stems from its extensive research and development efforts in machine learning, natural language processing, and computer vision.
Additionally,the company’s AI-powered products and services span a wide range of applications, from Google Search and Gmail to Google Photos and Google Maps.
Google’s open-source machine learning framework, TensorFlow, has become the industry standard for building and deploying AI models.
Moreover, Google’s acquisition of DeepMind Technologies has bolstered its AI capabilities, leading to breakthroughs in areas such as reinforcement learning and AlphaGo.
2. Amazon:
Amazon’s AI initiatives are integral to its core business operations, driving efficiency, personalization, and customer satisfaction.
The company’s AI-powered recommendation engine analyzes vast amounts of customer data to suggest products tailored to individual preferences, driving sales and enhancing user experience.
Additionally, Amazon’s investments in AI-driven logistics optimization have streamlined its supply chain operations, reducing costs and improving delivery times.
AWS offers a comprehensive suite of AI and machine learning services, including Amazon SageMaker, Amazon Recognition, and Amazon Comprehend, empowering businesses to harness the power of AI for their own applications.
8 Netflix Movies Redefining Artificial Intelligence – techovedas
3. Microsoft:
Microsoft’s AI strategy revolves around its Azure cloud platform, which provides a robust infrastructure for AI development and deployment.
Azure Machine Learning simplifies the process of building, training, and deploying AI models, while Azure Cognitive Services offers pre-trained AI models for vision, speech, language, and decision-making tasks.
Microsoft’s acquisition of LinkedIn has enabled the integration of AI-driven features into the professional networking platform, enhancing user engagement and productivity.
Additionally, Microsoft’s Project Brainwave initiative aims to accelerate AI workloads using specialized hardware, further solidifying its position in the AI space.
Read More: NVIDIA Crowns OpenAI King of AI with World’s First DGX H200 – techovedas
4. NVIDIA:
NVIDIA’s GPUs have become indispensable tools for AI researchers and developers, thanks to their unparalleled processing power and efficiency.
Additionally,the company’s CUDA programming platform and cuDNN library provide a robust framework for building and training deep learning models.
NVIDIA’s DGX system offers turnkey solutions for AI development and deployment, while the NVIDIA GPU Cloud provides a curated collection of AI software containers and workflows.
NVIDIA’s acquisition of Mellanox Technologies has strengthened its position in the AI infrastructure market, enabling high-speed data transfer and communication between GPU-accelerated systems.
5. IBM:
IBM’s Watson AI platform is renowned for its cognitive computing capabilities, enabling businesses to extract insights from unstructured data and make data-driven decisions.
Watson Assistant provides conversational AI capabilities for virtual agents and chatbots, while Watson Studio offers a collaborative environment for data scientists and developers to build and deploy AI models.
IBM’s acquisition of The Weather Company has enabled the integration of weather data into AI-driven applications, improving decision-making in industries such as agriculture, transportation, and retail.
Additionally, IBM Research is at the forefront of AI research, driving innovations in areas such as quantum computing, neuromorphic computing, and explainable AI.
Read more 6 Amazing Books on Generative AI That You Should Read in 2024 – techovedas
6. Tesla:
Tesla’s Autopilot system is a prime example of AI-driven innovation in the automotive industry, enabling semi-autonomous driving capabilities in Tesla vehicles.
Moreover,the company’s fleet of vehicles collects vast amounts of data, which are used to train AI models for improved performance and safety.
Tesla’s Full Self-Driving (FSD) package aims to achieve fully autonomous driving through continuous software updates and improvements.
Additionally, Tesla’s AI-driven approach extends beyond autonomous driving to include features like smart summon, autopark, and adaptive cruise control, enhancing the overall driving experience for Tesla owners.
7. Apple:
Apple’s integration of AI into its products and services focuses on enhancing user experiences while maintaining user privacy and security.
The company’s Siri virtual assistant uses natural language processing and machine learning to understand and respond to user commands, providing personalized assistance across Apple devices.
Moreover, Apple’s facial recognition technology, Face ID, relies on AI for biometric authentication, ensuring secure access to devices and sensitive data.
Furthermore, Apple’s acquisition of companies like Turi and VocalIQ has bolstered its AI capabilities, enabling advancements in areas such as predictive analytics, voice recognition, and natural language understanding.
8. Salesforce:
Salesforce’s Einstein AI platform is designed to empower businesses with AI-driven insights and recommendations, driving productivity, efficiency, and revenue growth.
The platform leverages machine learning to analyze customer data, predict outcomes, and automate routine tasks, enabling sales and marketing teams to focus on high-value activities.
Salesforce’s acquisition of companies like Tableau and MuleSoft has expanded its AI capabilities, enabling seamless integration of AI-driven analytics and data integration into its CRM platform.
Additionally, Salesforce’s Trailhead learning platform offers resources and training for businesses looking to upskill their workforce in AI and machine learning.
Conclusion
In conclusion, these 8 companies are at the forefront of the AI boom, leveraging their expertise, resources, and strategic investments to capitalize on the immense potential of AI technology.
As AI continues to reshape industries and drive innovation, these companies are well-positioned to lead the way forward, unlocking new opportunities and driving sustainable growth in the digital age.
April 28, 2024
IBM’s Watson AI platform is renowned for its cognitive computing capabilities, enabling businesses to extract insights from unstructured data and make data-driven decisions.
Watson Assistant provides conversational AI capabilities for virtual agents and chatbots, while Watson Studio offers a collaborative environment for data scientists and developers to build and deploy AI models.
IBM’s acquisition of The Weather Company has enabled the integration of weather data into AI-driven applications, improving decision-making in industries such as agriculture, transportation, and retail.
Additionally, IBM Research is at the forefront of AI research, driving innovations in areas such as quantum computing, neuromorphic computing, and explainable AI.
Read more 6 Amazing Books on Generative AI That You Should Read in 2024 – techovedas
6. Tesla:
Tesla’s Autopilot system is a prime example of AI-driven innovation in the automotive industry, enabling semi-autonomous driving capabilities in Tesla vehicles.
Moreover,the company’s fleet of vehicles collects vast amounts of data, which are used to train AI models for improved performance and safety.
Tesla’s Full Self-Driving (FSD) package aims to achieve fully autonomous driving through continuous software updates and improvements.
Additionally, Tesla’s AI-driven approach extends beyond autonomous driving to include features like smart summon, autopark, and adaptive cruise control, enhancing the overall driving experience for Tesla owners.
7. Apple:
Apple’s integration of AI into its products and services focuses on enhancing user experiences while maintaining user privacy and security.
The company’s Siri virtual assistant uses natural language processing and machine learning to understand and respond to user commands, providing personalized assistance across Apple devices.
Moreover, Apple’s facial recognition technology, Face ID, relies on AI for biometric authentication, ensuring secure access to devices and sensitive data.
Furthermore, Apple’s acquisition of companies like Turi and VocalIQ has bolstered its AI capabilities, enabling advancements in areas such as predictive analytics, voice recognition, and natural language understanding.
8. Salesforce:
Salesforce’s Einstein AI platform is designed to empower businesses with AI-driven insights and recommendations, driving productivity, efficiency, and revenue growth.
The platform leverages machine learning to analyze customer data, predict outcomes, and automate routine tasks, enabling sales and marketing teams to focus on high-value activities.
Salesforce’s acquisition of companies like Tableau and MuleSoft has expanded its AI capabilities, enabling seamless integration of AI-driven analytics and data integration into its CRM platform.
Additionally, Salesforce’s Trailhead learning platform offers resources and training for businesses looking to upskill their workforce in AI and machine learning.
Conclusion
In conclusion, these 8 companies are at the forefront of the AI boom, leveraging their expertise, resources, and strategic investments to capitalize on the immense potential of AI technology.
As AI continues to reshape industries and drive innovation, these companies are well-positioned to lead the way forward, unlocking new opportunities and driving sustainable growth in the digital age.
April 28, 2024
techovedas
Top 8 AI Hardware Companies in 2024 - techovedas
Explore the cutting-edge world of artificial intelligence through the lens of the top 8 AI hardware companies in 2023.
نقش فوق العاده مهم کمپانی NVidia در حوزه هوش مصنوعی و وابستگی آینده هوش مصنوعی جهان به آن 👆