Welcome, everyone. Today, let's delve into discussing two intricate, fascinating, and constantly evolving fields of artificial intelligence (AI): 'conventional AI' and 'generative AI'.

Artificial Intelligence has often been imagined as a ghost in the machine - human-like consciousnesses in silicon, akin to HAL 9000 from Space Odyssey or Ava in Ex Machina. But the truth is, today's AI - despite its complexity - is not conscious. Instead it works based on mathematical algorithms and a ton of data. A popular branch of AI is Machine Learning, where the machine is not explicitly programmed but instead taught, much like a child, to learn from its mistakes and improve its performance. Deep Learning, a subset of Machine Learning, uses artificial neural networks - a fascinating and ground-breaking technique inspired by human brain biology.

Companies like Google, Amazon, OpenAI, and Facebook have made extensive advancements in these areas. For instance, Google's DeepMind created AlphaGo, an AI which bested the reigning human champion in the notoriously intricate game of Go, in 2016.

Now, let's talk about the intriguing concept of Generative AI. It's a type of AI that creates from scratch - it can generate music, visual arts, poetry, prose, and even human-like text. Some outstanding examples include the DALL-E by OpenAI, that creates images from verbal descriptions, and Jukin Media that uses AI to compose original music.

But perhaps, one of the superior achievements in this field, created by OpenAI, is GPT-3. GPT-3 is notable for its size and predictability i.e., the huge amount of data it was trained on and its near-humanlike text synthesis capabilities. It's been utilized in various sectors from drafting emails to writing code autonomously.

The advancements in AI are happening at an exponential pace, and new tools and technologies are being developed each day that leverage the power of AI to address both big and small problems. Recently, Amazon Web Services launched Amazon SageMaker, a fully managed service that provides developers and data scientists the ability to build, train, and deploy machine learning models easily.

Despite all these impressive advancements, it's essential to remember that AI is still a tool, made by humans and dependent on human curation. Its capabilities remain governed by its programming and data inputs. Issues of bias, fairness, transparency, and data privacy are essential considerations amidst our excitement.

Lastly, AI is not here to replace humans but enhance us, allow us to automate mundane tasks, solve complex problems, bring creativity at scale, and even try to understand mysteries of the universe. It's an exciting era to witness, and the journey of AI is only just beginning. Let's continue to explore, create, and innovate together, for a future where tech and humanity complement each other harmoniously.

Until we meet again to venture into AI's latest developments, stay curious, and keep innovating!