This document provides an overview of Oracle Accelerated Data Science (ADS) capabilities for data science and machine learning. It discusses how ADS can be used to load and transform data from various sources, generate automated recommendations for data preprocessing, build and evaluate machine learning models using AutoML, and explain model predictions through global and local explanation techniques. Code samples are provided to demonstrate using ADS for tasks like loading data, generating feature importance plots and partial dependence plots, and explaining individual predictions.
[Code night] natural language proccessing and machine learningKenichi Sonoda
This document discusses BERT and its applications in natural language processing (NLP) tasks. It provides an overview of BERT, including its pre-training objectives of next sentence prediction and masked language modeling. It also demonstrates how to perform text classification with BERT using the Yahoo movie review dataset in Japanese. Finally, it provides some references and resources for using BERT in NLP.
20200812 Cbject Detection with OpenCV and CNNKenichi Sonoda
- OpenCV is an open source computer vision and machine learning software library. It was created by Intel and is used for tasks like image processing, video capture/analysis, and more.
- OpenCV supports languages like C++, Python, and Java and runs on many operating systems including Windows, Linux, Android, and iOS.
- The library contains functions for tasks like facial recognition, object detection, feature extraction, and more through the use of machine learning algorithms like SVM, neural networks, clustering, etc.
The document summarizes new features for the FRC Java programming software for 2011, including:
1. A new SmartDashboard class for conveniently logging diagnostic info to a remote display.
2. New motor safety classes that allow motors to automatically shut off if PWM signals stop, to improve safety.
3. Enhanced access to the driver station Cypress module for reading inputs like accelerometers.
4. A new ADXL345_I2C class for reading accelerometer data over I2C.
5. New image processing classes and capabilities.
6. Miscellaneous package and class changes.
Perth APAC Groundbreakers tour - SQL TechniquesConnor McDonald
This document discusses using SQL to perform various tasks like summarizing and transforming data, handling errors, and self-documenting queries. It provides examples of using pivot/unpivot clauses to change data orientation, query block naming to add descriptive comments to queries, and DBMS_ERRLOG to log errors from DML statements. It also discusses using partitioned outer joins to report bookings by hour including empty timeslots.
• Utilized SAS to make exploratory analysis of the data then found the optimal model by testing many different models. Made residual analysis and model diagnostics followed by forecast analysis.
• We used time plot, distribution analysis, correlation analysis, stationarity analysis to find optimal model. The forecast analysis proved that our model was good. It provided a simple parametric function that can be used to describe the volatility evolution. Also, it provided simple approach to calculating value at risk of a financial position in risk management.
- Oracle Database 20c Preview introduces several new capabilities including native blockchain tables, automated machine learning (AutoML), a native JSON binary representation, support for persistent memory, and enhancements to in-memory capabilities.
- A converged database allows for relational, JSON, XML, graph and spatial data to be stored and queried together using SQL and REST APIs.
- Oracle Database 19c is the current long term support release with extended lifecycle support until 2027, while the 20c preview provides early access to new innovations.
1. Oracle Cloud Infrastructure is Oracle's suite of IaaS and PaaS services.
2. Three reasons Oracle Cloud Infrastructure is adopted are good services at reasonable prices, robust security, and optimal data utilization.
3. For contract systems, there are two options tailored to customer usage: pay as you go or monthly flex plans. Check pricing estimates online.
[Code night] natural language proccessing and machine learningKenichi Sonoda
This document discusses BERT and its applications in natural language processing (NLP) tasks. It provides an overview of BERT, including its pre-training objectives of next sentence prediction and masked language modeling. It also demonstrates how to perform text classification with BERT using the Yahoo movie review dataset in Japanese. Finally, it provides some references and resources for using BERT in NLP.
20200812 Cbject Detection with OpenCV and CNNKenichi Sonoda
- OpenCV is an open source computer vision and machine learning software library. It was created by Intel and is used for tasks like image processing, video capture/analysis, and more.
- OpenCV supports languages like C++, Python, and Java and runs on many operating systems including Windows, Linux, Android, and iOS.
- The library contains functions for tasks like facial recognition, object detection, feature extraction, and more through the use of machine learning algorithms like SVM, neural networks, clustering, etc.
The document summarizes new features for the FRC Java programming software for 2011, including:
1. A new SmartDashboard class for conveniently logging diagnostic info to a remote display.
2. New motor safety classes that allow motors to automatically shut off if PWM signals stop, to improve safety.
3. Enhanced access to the driver station Cypress module for reading inputs like accelerometers.
4. A new ADXL345_I2C class for reading accelerometer data over I2C.
5. New image processing classes and capabilities.
6. Miscellaneous package and class changes.
Perth APAC Groundbreakers tour - SQL TechniquesConnor McDonald
This document discusses using SQL to perform various tasks like summarizing and transforming data, handling errors, and self-documenting queries. It provides examples of using pivot/unpivot clauses to change data orientation, query block naming to add descriptive comments to queries, and DBMS_ERRLOG to log errors from DML statements. It also discusses using partitioned outer joins to report bookings by hour including empty timeslots.
• Utilized SAS to make exploratory analysis of the data then found the optimal model by testing many different models. Made residual analysis and model diagnostics followed by forecast analysis.
• We used time plot, distribution analysis, correlation analysis, stationarity analysis to find optimal model. The forecast analysis proved that our model was good. It provided a simple parametric function that can be used to describe the volatility evolution. Also, it provided simple approach to calculating value at risk of a financial position in risk management.
- Oracle Database 20c Preview introduces several new capabilities including native blockchain tables, automated machine learning (AutoML), a native JSON binary representation, support for persistent memory, and enhancements to in-memory capabilities.
- A converged database allows for relational, JSON, XML, graph and spatial data to be stored and queried together using SQL and REST APIs.
- Oracle Database 19c is the current long term support release with extended lifecycle support until 2027, while the 20c preview provides early access to new innovations.
1. Oracle Cloud Infrastructure is Oracle's suite of IaaS and PaaS services.
2. Three reasons Oracle Cloud Infrastructure is adopted are good services at reasonable prices, robust security, and optimal data utilization.
3. For contract systems, there are two options tailored to customer usage: pay as you go or monthly flex plans. Check pricing estimates online.
Database@Home : The Future is Data DrivenTammy Bednar
These slides were presented during the Database@Home : Data-Driven Apps event. This session will discuss the importance of data to an organisation and the need to build applications where the value within that data can easily be exploited. To achieve that aim we need to start building applications that benefit from the flexibility of new development paradigms but don't create artificial barriers of complexity that stop us from easily responding to change within our organisations.
Oracle Cloud Infrastructure is Oracle's suite of IaaS and PaaS services. There are three main reasons for adopting OCI: 1) good services at appropriate prices, 2) robust security, and 3) optimal for data utilization. OCI offers two contract systems to suit customers' usage - Pay As You Go and Monthly Flex. Customers can check estimated prices online.
Database Basics with PHP -- Connect JS Conference October 17th, 2015Dave Stokes
This presentation covers the basics of using a relational database for PHP developers. Included are using Venn Diagrams, examining queries, and letting the database do the heavy lifting.
This document provides a summary of Biju Thomas, an Oracle Solutions Architect, and his presentation on exploring the Oracle database to help answer questions at the EBS application side. It outlines his experience and credentials working with Oracle databases and EBS applications. The presentation agenda covers using AWR to find expensive SQL, tying SQL to EBS jobs, common performance issues and resolutions, periodic database maintenance, and using multiple concurrent manager lanes for performance.
Graal is a dynamic meta-circular research compiler for Java that is designed for extensibility and modularity. One of its main distinguishing elements is the handling of optimistic assumptions obtained via profiling feedback and the representation of deoptimization guards in the compiled code. Truffle is a self-optimizing runtime system on top of Graal that uses partial evaluation to derive compiled code from interpreters. Truffle is suitable for creating high-performance implementations for dynamic languages with only moderate effort. The presentation includes a description of the Truffle multi-language API and performance comparisons within the industry of current prototype Truffle language implementations (JavaScript, Ruby, and R). Both Graal and Truffle are open source and form themselves research platforms in the area of virtual machine and programming language implementation (http://openjdk.java.net/projects/graal/).
This document provides an overview of new services and updates for Oracle Cloud Infrastructure in August 2020. It describes the new Gen 2 Exadata Cloud@Customer X8M system, which features faster CPUs, more memory and storage. It also discusses updates to billing models for several services including switching some resources to per-second billing. The document lists various service updates in July 2020 related to networking, security, and databases.
MySQL 8.0 provides significant performance and functionality enhancements over MySQL 5.7, including 3x better performance, new features like JSON support and window functions, and improved security, replication, and data dictionary capabilities. It underwent 2 years of development with over 5000 bugs fixed and new tests added.
This document provides an overview of Oracle Cloud Infrastructure (OCI) products and services including Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). It discusses various OCI services such as compute, storage, database, integration, and NoSQL database. It also provides release notes for May 2020 which describe new regions and services available in OCI. Finally, it shares examples of companies using and migrating to OCI to benefit from its performance, security, and cost effectiveness.
This document discusses how MySQL indexes and histograms can speed up queries. It begins with an introduction to the presenter and topic. The goal of reducing query response time is discussed. Methods for identifying inefficient queries are covered, including using the sys schema. The role of the MySQL optimizer in evaluating query plans is then explained. Different types of indexes that can be used to optimize queries are also outlined.
Oracle Cloud Infrastructure:
- Provides compute, storage, networking and other cloud infrastructure services.
- Offers various deployment options like virtual machines, bare metal servers and Exadata for running database and applications.
- Features industry-leading performance, security and support along with flexible pricing and service-level agreements.
Oracle Database House Party_Oracle Machine Learning to Pick a Good Inexpensiv...Charlie Berger
Ever seeking to use Oracle Converged Database technology with embedded machine learning algorithms to solve important problems of the day, our speakers will demonstrate how to use Oracle Machine Learning, Oracle Data Miner, a SQL Developer extension, APEX and ORDS REST Services to analyze wine data from Kaggle and pick a wine that is likely to be good (greater than 90 points) yet inexpensive (< $20). We will start with SQL Developer to import our data, explore it and build and apply machine learning models using Oracle Machine Learning, and then deploy the machine learning model in production applications using ORDS/REST services. Come see how much you can do today using Oracle’s Converged “AI” Database.
MySQL Goes to 8! FOSDEM 2020 Database Track, January 2nd, 2020Geir Høydalsvik
Here are the basic steps to clone a MySQL instance using the new CLONE command directly from SQL:
1. Connect to the source instance you want to clone from.
2. Issue the CLONE statement to create a new instance from the source. For example:
CLONE INSTANCE FROM 'mysql://user:password@source_host:3306/' TO 'mysql://user:password@target_host:3306/';
3. The clone operation will copy over the data files, redo logs and configuration from the source to the target instance.
4. Once complete, the new cloned instance is ready for use as a read replica or independent instance as needed.
By automating the provisioning
Databases are the heart of most PHP projects but roughly TWO PERCENT of PHP programmers have had any real training in Structured Query Language, SQL. Then they wonder why their queries perform poorly, why they get N+1 problems, and suddenly the database becomes the choke point of the project. This presentation will cover the basics of relational algebra (no algebra, math or calculus skills needed!!!!), how to think in sets with Venn Diagrams, and how to let the database do the heavy lifting for you. So if you want to write high performing database queries and be admired as a database deity by your co workers then you need to be in this session!
The document discusses Oracle NoSQL Database and its features. It provides an overview of NoSQL databases and data models in Oracle NoSQL including key-value, table, and JSON. It also describes Oracle NoSQL's architecture, which uses automatic data sharding and replication across storage nodes for high availability and scalability. Configuration and usage is simplified with libraries and command line tools.
Accelerating Deep Learning Training with BigDL and Drizzle on Apache Spark wi...Databricks
The BigDL framework scales deep learning for large data sets using Apache Spark. However there is significant scheduling overhead from Spark when running BigDL at large scale. In this talk we propose a new parameter manager implementation that along with coarse-grained scheduling can provide significant speedups for deep learning models like Inception, VGG etc. Aggregation functions like reduce or treeReduce that are used for parameter aggregation in Apache Spark (and the original MapReduce) are slow as the centralized scheduling and driver network bandwidth become a bottleneck especially in large clusters.
To reduce the overhead of parameter aggregation and allow for near-linear scaling, we introduce a new AllReduce operation, a part of the parameter manager in BigDL which is built directly on top of the BlockManager in Apache Spark. AllReduce in BigDL uses a peer-to-peer mechanism to synchronize and aggregate parameters. During parameter synchronization and aggregation, all nodes in the cluster play the same role and driver’s overhead is eliminated thus enabling near-linear scaling. To address the scheduling overhead we use Drizzle, a recently proposed scheduling framework for Apache Spark. Currently, Spark uses a BSP computation model, and notifies the scheduler at the end of each task. Invoking the scheduler at the end of each task adds overheads and results in decreased throughput and increased latency.
Drizzle introduces group scheduling, where multiple iterations (or a group) of iterations are scheduled at once. This helps decouple the granularity of task execution from scheduling and amortizes the costs of task serialization and launch. Finally we will present results from using the new AllReduce operation and Drizzle on a number of common deep learning models including VGG and Inception. Our benchmarks run on Amazon EC2 and Google DataProc will show the speedups and scalability of our implementation.
Oracle Database Migration to Oracle Cloud InfrastructureSinanPetrusToma
The document discusses various methods for migrating an on-premises Oracle database to Oracle Cloud Infrastructure (OCI). It outlines automation tools provided by Oracle like MV2ADB, MV2OCI and ZDM that can migrate databases with little to no downtime. The document also provides a decision tree to help choose the appropriate migration method based on factors like database version, character set, downtime requirements, etc. Common migration methods discussed are Data Guard, Transportable Tablespaces/Full using Data Pump or RMAN, backup/restore, and GoldenGate replication.
Nowadays, CPU microarchitecture is concealed from developers by compilers, VMs, etc.
Do Java developers need to know microarchitecture details of modern processors?
Or, does it like to learn quantum mechanics for cooking?
Are Java developers safe from leaking low-level microarchitecture details into high level application performance behaviour?
We will try to answer these questions by analyzing several Java examples.
Database@Home : The Future is Data DrivenTammy Bednar
These slides were presented during the Database@Home : Data-Driven Apps event. This session will discuss the importance of data to an organisation and the need to build applications where the value within that data can easily be exploited. To achieve that aim we need to start building applications that benefit from the flexibility of new development paradigms but don't create artificial barriers of complexity that stop us from easily responding to change within our organisations.
Oracle Cloud Infrastructure is Oracle's suite of IaaS and PaaS services. There are three main reasons for adopting OCI: 1) good services at appropriate prices, 2) robust security, and 3) optimal for data utilization. OCI offers two contract systems to suit customers' usage - Pay As You Go and Monthly Flex. Customers can check estimated prices online.
Database Basics with PHP -- Connect JS Conference October 17th, 2015Dave Stokes
This presentation covers the basics of using a relational database for PHP developers. Included are using Venn Diagrams, examining queries, and letting the database do the heavy lifting.
This document provides a summary of Biju Thomas, an Oracle Solutions Architect, and his presentation on exploring the Oracle database to help answer questions at the EBS application side. It outlines his experience and credentials working with Oracle databases and EBS applications. The presentation agenda covers using AWR to find expensive SQL, tying SQL to EBS jobs, common performance issues and resolutions, periodic database maintenance, and using multiple concurrent manager lanes for performance.
Graal is a dynamic meta-circular research compiler for Java that is designed for extensibility and modularity. One of its main distinguishing elements is the handling of optimistic assumptions obtained via profiling feedback and the representation of deoptimization guards in the compiled code. Truffle is a self-optimizing runtime system on top of Graal that uses partial evaluation to derive compiled code from interpreters. Truffle is suitable for creating high-performance implementations for dynamic languages with only moderate effort. The presentation includes a description of the Truffle multi-language API and performance comparisons within the industry of current prototype Truffle language implementations (JavaScript, Ruby, and R). Both Graal and Truffle are open source and form themselves research platforms in the area of virtual machine and programming language implementation (http://openjdk.java.net/projects/graal/).
This document provides an overview of new services and updates for Oracle Cloud Infrastructure in August 2020. It describes the new Gen 2 Exadata Cloud@Customer X8M system, which features faster CPUs, more memory and storage. It also discusses updates to billing models for several services including switching some resources to per-second billing. The document lists various service updates in July 2020 related to networking, security, and databases.
MySQL 8.0 provides significant performance and functionality enhancements over MySQL 5.7, including 3x better performance, new features like JSON support and window functions, and improved security, replication, and data dictionary capabilities. It underwent 2 years of development with over 5000 bugs fixed and new tests added.
This document provides an overview of Oracle Cloud Infrastructure (OCI) products and services including Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). It discusses various OCI services such as compute, storage, database, integration, and NoSQL database. It also provides release notes for May 2020 which describe new regions and services available in OCI. Finally, it shares examples of companies using and migrating to OCI to benefit from its performance, security, and cost effectiveness.
This document discusses how MySQL indexes and histograms can speed up queries. It begins with an introduction to the presenter and topic. The goal of reducing query response time is discussed. Methods for identifying inefficient queries are covered, including using the sys schema. The role of the MySQL optimizer in evaluating query plans is then explained. Different types of indexes that can be used to optimize queries are also outlined.
Oracle Cloud Infrastructure:
- Provides compute, storage, networking and other cloud infrastructure services.
- Offers various deployment options like virtual machines, bare metal servers and Exadata for running database and applications.
- Features industry-leading performance, security and support along with flexible pricing and service-level agreements.
Oracle Database House Party_Oracle Machine Learning to Pick a Good Inexpensiv...Charlie Berger
Ever seeking to use Oracle Converged Database technology with embedded machine learning algorithms to solve important problems of the day, our speakers will demonstrate how to use Oracle Machine Learning, Oracle Data Miner, a SQL Developer extension, APEX and ORDS REST Services to analyze wine data from Kaggle and pick a wine that is likely to be good (greater than 90 points) yet inexpensive (< $20). We will start with SQL Developer to import our data, explore it and build and apply machine learning models using Oracle Machine Learning, and then deploy the machine learning model in production applications using ORDS/REST services. Come see how much you can do today using Oracle’s Converged “AI” Database.
MySQL Goes to 8! FOSDEM 2020 Database Track, January 2nd, 2020Geir Høydalsvik
Here are the basic steps to clone a MySQL instance using the new CLONE command directly from SQL:
1. Connect to the source instance you want to clone from.
2. Issue the CLONE statement to create a new instance from the source. For example:
CLONE INSTANCE FROM 'mysql://user:password@source_host:3306/' TO 'mysql://user:password@target_host:3306/';
3. The clone operation will copy over the data files, redo logs and configuration from the source to the target instance.
4. Once complete, the new cloned instance is ready for use as a read replica or independent instance as needed.
By automating the provisioning
Databases are the heart of most PHP projects but roughly TWO PERCENT of PHP programmers have had any real training in Structured Query Language, SQL. Then they wonder why their queries perform poorly, why they get N+1 problems, and suddenly the database becomes the choke point of the project. This presentation will cover the basics of relational algebra (no algebra, math or calculus skills needed!!!!), how to think in sets with Venn Diagrams, and how to let the database do the heavy lifting for you. So if you want to write high performing database queries and be admired as a database deity by your co workers then you need to be in this session!
The document discusses Oracle NoSQL Database and its features. It provides an overview of NoSQL databases and data models in Oracle NoSQL including key-value, table, and JSON. It also describes Oracle NoSQL's architecture, which uses automatic data sharding and replication across storage nodes for high availability and scalability. Configuration and usage is simplified with libraries and command line tools.
Accelerating Deep Learning Training with BigDL and Drizzle on Apache Spark wi...Databricks
The BigDL framework scales deep learning for large data sets using Apache Spark. However there is significant scheduling overhead from Spark when running BigDL at large scale. In this talk we propose a new parameter manager implementation that along with coarse-grained scheduling can provide significant speedups for deep learning models like Inception, VGG etc. Aggregation functions like reduce or treeReduce that are used for parameter aggregation in Apache Spark (and the original MapReduce) are slow as the centralized scheduling and driver network bandwidth become a bottleneck especially in large clusters.
To reduce the overhead of parameter aggregation and allow for near-linear scaling, we introduce a new AllReduce operation, a part of the parameter manager in BigDL which is built directly on top of the BlockManager in Apache Spark. AllReduce in BigDL uses a peer-to-peer mechanism to synchronize and aggregate parameters. During parameter synchronization and aggregation, all nodes in the cluster play the same role and driver’s overhead is eliminated thus enabling near-linear scaling. To address the scheduling overhead we use Drizzle, a recently proposed scheduling framework for Apache Spark. Currently, Spark uses a BSP computation model, and notifies the scheduler at the end of each task. Invoking the scheduler at the end of each task adds overheads and results in decreased throughput and increased latency.
Drizzle introduces group scheduling, where multiple iterations (or a group) of iterations are scheduled at once. This helps decouple the granularity of task execution from scheduling and amortizes the costs of task serialization and launch. Finally we will present results from using the new AllReduce operation and Drizzle on a number of common deep learning models including VGG and Inception. Our benchmarks run on Amazon EC2 and Google DataProc will show the speedups and scalability of our implementation.
Oracle Database Migration to Oracle Cloud InfrastructureSinanPetrusToma
The document discusses various methods for migrating an on-premises Oracle database to Oracle Cloud Infrastructure (OCI). It outlines automation tools provided by Oracle like MV2ADB, MV2OCI and ZDM that can migrate databases with little to no downtime. The document also provides a decision tree to help choose the appropriate migration method based on factors like database version, character set, downtime requirements, etc. Common migration methods discussed are Data Guard, Transportable Tablespaces/Full using Data Pump or RMAN, backup/restore, and GoldenGate replication.
Nowadays, CPU microarchitecture is concealed from developers by compilers, VMs, etc.
Do Java developers need to know microarchitecture details of modern processors?
Or, does it like to learn quantum mechanics for cooking?
Are Java developers safe from leaking low-level microarchitecture details into high level application performance behaviour?
We will try to answer these questions by analyzing several Java examples.
Similar to 20200402 oracle cloud infrastructure data science (20)
This document discusses neural networks and deep learning concepts such as artificial neurons, edges, weights, biases, activation functions, backpropagation, optimization algorithms like stochastic gradient descent, and neural network architectures like convolutional neural networks. It provides examples of neural network calculations and discusses tasks like image classification using datasets such as ImageNet and CIFAR-10.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics