2. Ivan so
● 18 years of SEO and WordPress experience
● Built 50 site to test SEO
● Handled over 400 WordPress design and
● Lead organiser of WordCamp, co-organiser
of HK WP meetup and HK elementor
3. My bio
● 5 times amazon ebook best sellers
● Mailchimp HK partner
● Shopify Partner
8. Artiﬁcial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring
information—demonstrated by machines, as opposed to intelligence displayed by
non-human animals and humans. Example tasks in which this is done include speech
recognition, computer vision, translation between (natural) languages, as well as
other mappings of inputs.
AI applications include advanced web search engines (e.g., Google Search),
recommendation systems (used by YouTube, Amazon and Netﬂix), understanding
human speech (such as Siri and Alexa), self-driving cars (e.g., Waymo), generative or
creative tools (ChatGPT and AI art), automated decision-making and competing at
the highest level in strategic game systems (such as chess and Go).
17. Generative AI refers to a set of deep-learning technologies that use existing content, such
as text, audio, or images, to create new plausible content that previously would have relied
on humans. Generative AI is driven by unsupervised and semi-supervised machine
learning algorithms capable of identifying underlying patterns present in the input to
generate similar content, delivering innovative results without human thought processes
Well-known examples of generative AI models include Open AI's GPT-3 (text generator)
and DALL-E (text-to-image generator) and Google's BERT (language model). Various
techniques are utilized by generative AI algorithms, and the two most widely used models
are generative adversarial networks (GANs) and transformer-based models. Another
popular technique is variational auto-encoders (VAEs).
21. GPT 3 - 175B
In the context of deep learning models, a parameter refers to a variable that a machine learning algorithm
learns from data during the training process.
In a neural network, for example, parameters are weights and biases assigned to each neuron in the
network. These weights and biases determine how input data is transformed as it passes through the
network, and they are adjusted during the training process in order to minimize a loss function and
improve the accuracy of the model's predictions.
82. Exercise Write a short paragraph about a topic of
their choice, then have them rewrite the
same paragraph using different vocabulary
and sentence structure.
This exercise will help them understand how
to rephrase and reframe their writing to
create unique content.
A random seed (or seed state, or just seed) is a number (or vector) used to initialize a
pseudorandom number generator. For a seed to be used in a pseudorandom number
generator, it does not need to be random
Think of it like this: by default, Midjourney selects a random seed value in each
generation process that deﬁnes the type of noise pattern Midjourney uses to
generate the image you want. This seed value is simply a number used to introduce a
random but consistent element of “noise” into the process.