Two Voice Devs

The Alexa Developer Rewards Program (ADR) is shutting down, leaving many developers wondering about the future of Alexa skills. Mark and Allen discuss the implications of this change, explore alternative monetization options, and share their thoughts on the future of skill development.

Timestamps:

0:00 - Intro and announcement of the ADR program ending

1:45 - History of the ADR program and its impact on skill development

7:13 - Discussion of the Skill Developer Accelerator Program (SDAP) and Skill Coach

14:04 - Status of AWS credits for skill developers

15:10 - Incentives for building skills in the absence of the ADR program

21:30 - Cost-benefit analysis and the future of skill development

25:48 - Call to action: Share your thoughts on the ADR program ending and the future of skills

Join the conversation and let us know what you think!E

As large language models (LLMs) become increasingly powerful, ensuring their responsible use is crucial. In this episode of Two Voice Devs, Allen and Mark delve into Google's Gemini LLM, specifically its built-in safety features designed to prevent harmful outputs like harassment, hate speech, sexually explicit content, and dangerous information.

Join them as they discuss:

(00:01:55) The importance of safety features in LLMs and Google's approach to responsible AI.

(00:03:08) A walkthrough of Gemini's safety settings in AI Studio, including the four categories of evaluation and developer control options.

(00:06:51) Examples of how Gemini flags potentially harmful prompts and responses, and how developers can adjust settings to control output.

(00:08:55) A deep dive into the API, exploring the parameters and responses related to safety features.

(00:19:38) The challenges of handling incomplete responses due to safety violations and the need for better recovery strategies.

(00:26:47) The importance of industry standards and finer-grained control for responsible AI development.

(00:29:00) A call to action for developers and conversation designers to discuss and collaborate on best practices for handling safety issues in LLMs.

This episode offers valuable insights for developers working with LLMs and anyone interested in the future of responsible AI. Tune in and share your thoughts on how we can build safer and more ethical AI systems!

In this episode of Two Voice Devs, Mark and Allen discuss how developers can leverage AI tools like ChatGPT to improve their workflow. Mark shares his experience using ChatGPT to generate an OpenAPI specification from TypeScript types, saving him significant time and effort. They discuss the benefits and limitations of using AI for code generation, emphasizing the importance of understanding the generated code and maintaining healthy skepticism.

Timestamps:

00:00:00 Introduction

00:00:49 Using AI as a developer tool

00:01:17 Generating OpenAPI specifications with ChatGPT

00:04:02 Mark's prompt and TypeScript types

00:05:37 Reviewing the generated OpenAPI specification

00:07:12 Adding request examples with ChatGPT

00:10:11 Benefits and limitations of AI code generation

00:13:43 Using AI tools for learning and understanding code

00:17:39 Trusting AI-generated code and potential for bias

00:19:04 Integrating AI tools into the development workflow

00:22:38 The future of AI in software development

00:23:17 Programmers as problem solvers, not just code writers

00:25:41 AI as a tool in the developer's toolbox

00:26:07 Call to action: Share your experiences with AI tools

This episode offers valuable insights for developers interested in exploring the potential of AI to enhance their productivity and efficiency.

Join us on Two Voice Devs as we chat with Xavi, Head of Cloud Infrastructure at Voiceflow, about the exciting new Voiceflow Functions feature and the future of conversational AI development. Xavi shares his journey into the world of bots and assistants, dives into the technology behind Voiceflow's infrastructure, and explains how functions empower developers to create custom, reusable components for their conversational experiences.

Timestamps:

Whether you're a seasoned developer or just getting started with conversational AI, this episode offers valuable insights into the evolving landscape of bot development and the powerful capabilities of Voiceflow.

In this episode of Two Voice Devs, Allen Firstenberg and Roger Kibbe explore the rising trend of local LLMs, smaller language models designed to run on personal devices instead of relying on cloud-based APIs. They discuss the advantages and disadvantages of this approach, focusing on data privacy, control, cost efficiency, and the unique opportunities it presents for developers. They also delve into the importance of fine-tuning these smaller models for specific tasks, enabling them to excel in areas like legal contract analysis and mobile app development.

The conversation dives into various popular local LLM models, including:

Learn more:

Timestamps:

00:00:00: Introduction and welcome back to Roger Kibbe.

00:01:31: Roger discusses his career path and his passion for voice and AI.

00:06:33: The discussion turns to the larger vs. smaller LLMs.

00:13:52: Understanding key terminology like quantization and fine-tuning.

00:20:58: Roger shares his favorite local LLM models.

00:25:14: Discussing the strengths and weaknesses of smaller models like Gemma.

00:30:32: Exploring the benefits and challenges of running LLMs locally.

00:39:15: The value of local LLMs for developers and individual learning.

00:40:29: The impact of local LLMs on mobile devices and app development.

00:49:27: Closing thoughts and call for audience feedback.

Join Allen and Roger as they explore the exciting potential of local LLMs and how they might revolutionize the development landscape!

Join Allen and Mark on Two Voice Devs as they dive into the world of Large Action Models (LAMs) and explore their potential to revolutionize how we build chatbots and voice assistants.

Inspired by Braden Ream's article "How Large Action Models Work and Change the Way We Build Chatbots and Agents," the discussion dissects the core functions of conversational AI - understand, decide, and respond - and examines how LAMs might fit into this framework.

Allen and Mark also compare and contrast LAMs with Large Language Models (LLMs) and Natural Language Understanding (NLU), highlighting the strengths and limitations of each approach.

Tune in to hear their insights on:

Whether you're a seasoned developer or just curious about the future of conversational AI, this episode offers a thought-provoking discussion on the potential of LAMs and the challenges that lie ahead.

Be sure to share your thoughts in the comments below!

Additional Info:

Google's Gemini 1.5 is here, boasting a mind-blowing 1 million token context window! 🤯 Join Allen and Linda as they dive deep into this experimental AI, exploring its capabilities, limitations, and potential use cases. 🤔

They share their experiences testing Gemini 1.5 with original content, including Two Voice Devs transcripts and synthetic videos, and discuss the challenges of finding data that hasn't already been used to train the AI. 🧐

Get ready for a lively discussion on hallucinations, the future of content creation, and the ethical questions surrounding these powerful language models. 🤖

More info:

* https://blog.google/technology/ai/google-gemini-next-generation-model-february-2024/

* https://developers.googleblog.com/2024/02/gemini-15-available-for-private-preview-in-google-ai-studio.html

* https://openai.com/sora

Timestamps:

00:00:00 Introduction

00:01:05 Notable features of Gemini 1.5

00:02:57 What is a token?

00:06:39 Linda's test with Danish citizenship PDF

00:09:33 Allen's test with Les Miserables and needle in a haystack

00:12:27 Testing with Data Portability API data

00:14:28 Linda's test with YouTube search history and Netflix recommendations

00:17:44 Allen's test with Two Voice Devs transcripts

00:21:32 Issues with counting and hallucinations

00:24:21 Testing with OpenAI's Sora AI synthetic videos

00:30:05 Ethical questions and the future of content creation

00:31:50 Potential use cases for large context windows

00:36:34 API limitations and challenges

00:37:39 Performance and cost considerations

00:41:34 Comparison with retrieval augmented generation and vector databases

00:44:21 Generating summaries and markers from this transcript

Leave your thoughts and questions in the comments below!

In this episode of Two Voice Devs, hosts Allen Firstenberg and Mark Tucker discuss Gemini, Google's latest name for its Generative AI... stuff. Originally known as separate products including Bard and Duet AI, Gemini encompasses a suite of AI tools, including chatbots, product-specific assistants, models, and APIs that developers can use for various tasks. The discussion covers how Gemini compares with offerings from other companies such as OpenAI and Microsoft, including visible similarities and differences. The show concludes by answering the question about why developers should care about this rename with a call to explore possibilities with AI tools like Gemini to let us create more natural and user-friendly interfaces.

Learn more:

00:04 Introduction and Catching Up

00:55 Exploring the Gemini Model

04:09 Gemini vs OpenAI: A Comparison

10:20 Understanding the Gemini Branding

12:00 The Developer's Perspective on Gemini

17:46 Closing Thoughts and Future Discussions

In this episode of Two Voice Devs, hosts Allen Firstenberg and Mark Tucker discuss the CSS Speech Module Level 1 Candidate Recommendation Draft, a standard that enables webpages to talk, developed in collaboration with the voice browser activity. They explore its features including the 'aural' box model concept, voice families, earcons and more, drawing parallels with SSML and highlight its innovative approach to web accessibility complementing screen readers. Despite acknowledging its potential, they address some of its key omissions such as phonemes and the lack of a background audio feature.

00:04 Introduction and Welcome

01:14 Exploring the Concept of Webpages Talking

03:00 Deep Dive into CSS Speech Module

03:48 Understanding the Scope of CSS Speech Module

04:27 The Evolution of Voice Interaction

05:22 Comparing CSS Speech with SSML

07:13 The Power of CSS in Voice Development

22:49 The Impact of Voice Balance Property

29:20 The Limitations of CSS Speech

39:37 The Future of CSS Speech

42:50 Conclusion and Final Thoughts

Forget Apps! Talking to this Orange Cube Could Change Everything

Is the app model broken? The creators of Rabbit R1, a new voice-first device, certainly think so. In this episode of Two Voice Devs, Mark and Allen break down this innovative device and its potential to change how we interact with technology. What do developers think about the technology underlying RabbitOS? You may be surprised!

Key topics:

Additional thoughts:

Is Rabbit R1 a game-changer or just a gimmick? Let us know your thoughts in the comments!