🤖
AI Wiki
Gradient PlatformDocsGet Started FreeContact Sales
  • Artificial Intelligence Wiki
  • Topics
    • Accuracy and Loss
    • Activation Function
    • AI Chips for Training and Inference
    • Artifacts
    • Artificial General Intelligence (AGI)
    • AUC (Area under the ROC Curve)
    • Automated Machine Learning (AutoML)
    • CI/CD for Machine Learning
    • Comparison of ML Frameworks
    • Confusion Matrix
    • Containers
    • Convergence
    • Convolutional Neural Network (CNN)
    • Datasets and Machine Learning
    • Data Science vs Machine Learning vs Deep Learning
    • Distributed Training (TensorFlow, MPI, & Horovod)
    • Generative Adversarial Network (GAN)
    • Epochs, Batch Size, & Iterations
    • ETL
    • Features, Feature Engineering, & Feature Stores
    • Gradient Boosting
    • Gradient Descent
    • Hyperparameter Optimization
    • Interpretability
    • Jupyter Notebooks
    • Kubernetes
    • Linear Regression
    • Logistic Regression
    • Long Short-Term Memory (LSTM)
    • Machine Learning Operations (MLOps)
    • Managing Machine Learning Models
    • ML Showcase
    • Metrics in Machine Learning
    • Machine Learning Models Explained
    • Model Deployment (Inference)
    • Model Drift & Decay
    • Model Training
    • MNIST
    • Overfitting vs Underfitting
    • Random Forest
    • Recurrent Neural Network (RNN)
    • Reproducibility in Machine Learning
    • REST and gRPC
    • Serverless ML: FaaS and Lambda
    • Synthetic Data
    • Structured vs Unstructured Data
    • Supervised, Unsupervised, & Reinforcement Learning
    • TensorBoard
    • Tensor Processing Unit (TPU)
    • Transfer Learning
    • Weights and Biases
Powered by GitBook
On this page
  • What is Artificial General Intelligence?
  • Does AGI Exist Today?
  • Impact on society

Was this helpful?

  1. Topics

Artificial General Intelligence (AGI)

PreviousArtifactsNextAUC (Area under the ROC Curve)

Last updated 5 years ago

Was this helpful?

What is Artificial General Intelligence?

The form of AI that exists today is considered narrow AI. It is adept at solving specific tasks limited to specific domains but it cannot be extended to perform tasks in other domains easily (see ).

In contrast, Artificial General Intelligence represents an advanced version of AI capable of performing general tasks often associated with human intelligence. This requires a combination of flexible "thinking" and adaptability -- it also requires the ability to reason and the concept of memory.

Does AGI Exist Today?

AGI does not exist yet. Today it is merely a field of study and a popular topic in science fiction. Many experts believe we are a decade or so away from AGI assuming current investment does not dissipate. In terms of research trajectories, many believe that is a viable path towards AGI. There are several organizations that are actively working to "solve" AGI such as OpenAI and DeepMind.

Impact on society

AI has already made a tremendous impact on society. Yet AI remains constrained in such a way that the need for human labor is still necessary even in fields with a high degree of automation and AI. Overall, the number of jobs has actually increased in many industries impacted by AI. This is due in part to a phenomenon called the Automation Paradox. Here's a great snippet from the on the rise of AI in the legal industry:

Take the legal industry as an example. Computers are taking over some of the work of lawyers and paralegals, and they’re doing a better job of it. For over a decade, computers have been used to sort through corporate documents to find those that are relevant to lawsuits. This process — called “discovery” in the profession — can run up millions of dollars in legal bills, but electronic methods . Moreover, the computers are often more accurate than humans: In one , software correctly found 95 percent of the relevant documents, while humans identified only 51 percent."

Many believe that AGI will have a much greater impact than the impact of the form of narrow AI we have today. If AGI truly does render human labor obsolete the impact would be profound—with vast societal ramifications. Rising fears of massive unemployment have led to the discussion of Universal Basic Income (UBI) which would provide regular payments to everyone in society. It is important to note that there are many positive potential outcomes and that these types of fears are often misplaced. Several predictions of the impact of automation and AI that exist today have been proven false (eg the legal discovery example above). Societal shifts at this scale are endlessly complex, often counter-intuitive, and generally difficult to theorize.

Transfer Learning
Atlantic
can erase the vast majority of those costs
study
Reinforcement Learning