NEWS
Josh Constine leaves TechCrunch for VC fund SignalFire
How do you leave the place that made you? You figure out what it made you for. TechCrunch made me a part of the startup ecosystem I love. Now it’s time to put that love into action to help a new generation of entrepreneurs build their dreams and tell their stories.
So it’s “TC to VC” for me. After 8.5 years at TechCrunch and 10 in tech journalism, I’m leaving today to join the venture team at VC fund SignalFire. I’m going to be a principal investor and their head of content.
I’ll be seeking out inspiring new companies, doing deals (when I’m eventually up to speed) and providing pitch workshops based on countless interviews for TechCrunch. Thankfully, I’ll also still get to write. We’re going to find out what founders really want to learn and produce that content to help them form, evolve and grow their companies. I’m doing my signature bounce & smile with excitement.
Where to follow my writing
You’ll still be able to follow my writing as well as my journey into VC on my newsletter Moving Product at constine.substack.com as well as on Twitter: @JoshConstine. No way I could just suddenly shut up about startups! If you’re building something, you can always reach me at joshsc [at] gmail.com
On the newsletter you can read a deeper explanation for why I picked SignalFire. I also just published the first real issue of Moving Product on how quarantine is “loaning” concurrent users to startups that will help the new wave of synchronous apps snowball to sustainability, plus commentary from top product thinkers on Facebook’s new Rooms.
Why I chose SignalFire?
I was drawn to SignalFire because it’s built like the startups I love writing about: to solve a need. Entrepreneurs need tactical advantages in areas like recruiting, where they spend most of their time, and expert advice on specific problems they’re facing.
That’s why SignalFire spent six years in stealth building its recruitment prediction and market data analysis engine called Beacon. It can spot deal opportunities for SignalFire’s new $200 million seed and $300 million breakout funds while helping the portfolio hire smarter. Then SignalFire assembled more than 80 top experts, like Instagram’s founders, for its invested advisor network. Traditional funds need partners to exhaust their social capital asking for favors from friends to help their portfolio. SignalFire’s model sees its advisors share in the returns of the fund, so they’re sustainably motivated to assist.
SignalFire’s founder and CEO Chris Farmer was also willing to invest in me, figuratively. I’ve written about thousands of startups but I’ve never funded one. He and his team have offered to mentor me as I learn the art and science of investing. They also accept me for my opinionated, outspoken self. Instead of constricting my voice, the plan is to harness it to highlight new ideas and proven methods for building companies. I wrote this post on my newsletter with a deeper look at why I picked SignalFire and how its modernized approach to venture works.
What makes TechCrunch different
Of the 3,600 articles I’ve written for TechCrunch, this was the hardest.
TechCrunch gave me the platform to make an impact and the freedom to say what I believe. That’s a rare opportunity in journalism, but especially important for covering startups. TechCrunch writes about things that haven’t happened yet. There are often no objective facts by which to judge an early-stage company. Whether you decide to cover them or not, and the tone of your analysis, depends on having conviction about whether the world needs something or not, if the product is built right and if the team has what it takes.
If you rely on others’ signals about what matters, whether in the form of traction or investment, you’ll be late to the story. That means editors have to trust their writers’ intuition. At TechCrunch, that trust never wavered.
Eric Eldon, Alexia Tsotsis and Matthew Panzarino put their absolute faith in our team. That gave me a chance to write the first-ever coverage of startups like Robinhood before its seed round, and SnappyCam before it was acquired by Apple and turned into iPhone burst fire. My editors also never shied away from confrontations with the tech giants, like my investigation into Facebook paying teens for their data that caused it to shut down its Onavo tool, or my exposé on Bing suggesting child abuse imagery in search results that led it to overhaul its systems.
I’ll always be indebted to Eric Eldon, who gave a freshly graduated cybersociologist with no experience his first shot at blogging back at Inside Facebook. Editors like Alexia Tsotsis and Matthew Panzarino helped me develop a more critical voice without sterilizing my personality. And all my fellow writers over the years, including Zack Whittaker and Sarah Perez, pushed me to hustle, whether that meant pontificating on new product launches or exposing industry abuse. If my departure from journalism elicits a sigh of relief from the companies in my cross-hairs, I know I did my job. The TechCrunch business and events team have turned Disrupt into the tech industry’s reunion. I appreciate them giving me the chance to learn public speaking, from the most heartfelt moments to the cringiest. And really, I owe them the rest of my life, too, since I met my wife Andee at a Disrupt after-party.
Treating writing like a sport to be won kept me cranking all these years, and I’m grateful for Techmeme offering a scoreboard for extra motivation. I’ll unhumbly admit it’s nice to hang up my jersey while ranked No. 1. My gratitude to Jane Manchun Wong for furnishing so many scoops over the years, and to all my other sources. It’s been fun competing and collaborating with my favorite other reporters, and I know Taylor Lorenz, Casey Newton and Mike Isaac will keep a close eye on tech’s trends and travesties.
But most of all, I want to extend an enormous thank you to…you. To everyone who has read or shared my articles over the years. I woke up each day with a sense of duty to you, and felt proud to say “I fight for the user” like Tron. What makes this industry special is how the community refuses to treat it as zero-sum. We grow the pie together, and everyone knows their competitor today could be their future co-founder. That makes us willing to share and learn together. I believe no recession, correction or bubble-burst will change that.
So I’ll leave you with a final thought that’s made my life so fulfilling: If you have the privilege or create the opportunity, turn your passion into your profession.
Specialize. Learn. Then make what you want. If you can find some niche you’re endlessly interested in, that’s growing in importance, and at least someone somewhere earns money from, you’ll become essential. Not necessarily today. But that’s the beauty of writing — it teaches you while proving to others what you’ve been taught. No matter what it is, blog about it once a week. In time you’ll become an expert, and be recognized as one. Then you’ll have the power to adapt to the future, however feels most graceful.
Keep up with my writing on my newsletter at constine.substack.com, stay in touch on Twitter, and reach out at joshsc [at] gmail.com
NEWS
OpenAI Introduces Fine-Tuning for GPT-4 and Enabling Customized AI Models
OpenAI has today announced the release of fine-tuning capabilities for its flagship GPT-4 large language model, marking a significant milestone in the AI landscape. This new functionality empowers developers to create tailored versions of GPT-4 to suit specialized use cases, enhancing the model’s utility across various industries.
Fine-tuning has long been a desired feature for developers who require more control over AI behavior, and with this update, OpenAI delivers on that demand. The ability to fine-tune GPT-4 allows businesses and developers to refine the model’s responses to better align with specific requirements, whether for customer service, content generation, technical support, or other unique applications.
Why Fine-Tuning Matters
GPT-4 is a very flexible model that can handle many different tasks. However, some businesses and developers need more specialized AI that matches their specific language, style, and needs. Fine-tuning helps with this by letting them adjust GPT-4 using custom data. For example, companies can train a fine-tuned model to keep a consistent brand tone or focus on industry-specific language.
Fine-tuning also offers improvements in areas like response accuracy and context comprehension. For use cases where nuanced understanding or specialized knowledge is crucial, this can be a game-changer. Models can be taught to better grasp intricate details, improving their effectiveness in sectors such as legal analysis, medical advice, or technical writing.
Key Features of GPT-4 Fine-Tuning
The fine-tuning process leverages OpenAI’s established tools, but now it is optimized for GPT-4’s advanced architecture. Notable features include:
- Enhanced Customization: Developers can precisely influence the model’s behavior and knowledge base.
- Consistency in Output: Fine-tuned models can be made to maintain consistent formatting, tone, or responses, essential for professional applications.
- Higher Efficiency: Compared to training models from scratch, fine-tuning GPT-4 allows organizations to deploy sophisticated AI with reduced time and computational cost.
Additionally, OpenAI has emphasized ease of use with this feature. The fine-tuning workflow is designed to be accessible even to teams with limited AI experience, reducing barriers to customization. For more advanced users, OpenAI provides granular control options to achieve highly specialized outputs.
Implications for the Future
The launch of fine-tuning capabilities for GPT-4 signals a broader shift toward more user-centric AI development. As businesses increasingly adopt AI, the demand for models that can cater to specific business needs, without compromising on performance, will continue to grow. OpenAI’s move positions GPT-4 as a flexible and adaptable tool that can be refined to deliver optimal value in any given scenario.
By offering fine-tuning, OpenAI not only enhances GPT-4’s appeal but also reinforces the model’s role as a leading AI solution across diverse sectors. From startups seeking to automate niche tasks to large enterprises looking to scale intelligent systems, GPT-4’s fine-tuning capability provides a powerful resource for driving innovation.
OpenAI announced that fine-tuning GPT-4o will cost $25 for every million tokens used during training. After the model is set up, it will cost $3.75 per million input tokens and $15 per million output tokens. To help developers get started, OpenAI is offering 1 million free training tokens per day for GPT-4o and 2 million free tokens per day for GPT-4o mini until September 23. This makes it easier for developers to try out the fine-tuning service.
As AI continues to evolve, OpenAI’s focus on customization and adaptability with GPT-4 represents a critical step in making advanced AI accessible, scalable, and more aligned with real-world applications. This new capability is expected to accelerate the adoption of AI across industries, creating a new wave of AI-driven solutions tailored to specific challenges and opportunities.
This Week in Search News: Simple and Easy-to-Read Update
Here’s what happened in the world of Google and search engines this week:
1. Google’s June 2024 Spam Update
Google finished rolling out its June 2024 spam update over a period of seven days. This update aims to reduce spammy content in search results.
2. Changes to Google Search Interface
Google has removed the continuous scroll feature for search results. Instead, it’s back to the old system of pages.
3. New Features and Tests
- Link Cards: Google is testing link cards at the top of AI-generated overviews.
- Health Overviews: There are more AI-generated health overviews showing up in search results.
- Local Panels: Google is testing AI overviews in local information panels.
4. Search Rankings and Quality
- Improving Rankings: Google said it can improve its search ranking system but will only do so on a large scale.
- Measuring Quality: Google’s Elizabeth Tucker shared how they measure search quality.
5. Advice for Content Creators
- Brand Names in Reviews: Google advises not to avoid mentioning brand names in review content.
- Fixing 404 Pages: Google explained when it’s important to fix 404 error pages.
6. New Search Features in Google Chrome
Google Chrome for mobile devices has added several new search features to enhance user experience.
7. New Tests and Features in Google Search
- Credit Card Widget: Google is testing a new widget for credit card information in search results.
- Sliding Search Results: When making a new search query, the results might slide to the right.
8. Bing’s New Feature
Bing is now using AI to write “People Also Ask” questions in search results.
9. Local Search Ranking Factors
Menu items and popular times might be factors that influence local search rankings on Google.
10. Google Ads Updates
- Query Matching and Brand Controls: Google Ads updated its query matching and brand controls, and advertisers are happy with these changes.
- Lead Credits: Google will automate lead credits for Local Service Ads. Google says this is a good change, but some advertisers are worried.
- tROAS Insights Box: Google Ads is testing a new insights box for tROAS (Target Return on Ad Spend) in Performance Max and Standard Shopping campaigns.
- WordPress Tag Code: There is a new conversion code for Google Ads on WordPress sites.
These updates highlight how Google and other search engines are continuously evolving to improve user experience and provide better advertising tools.
Facebook Faces Yet Another Outage: Platform Encounters Technical Issues Again
Uppdated: It seems that today’s issues with Facebook haven’t affected as many users as the last time. A smaller group of people appears to be impacted this time around, which is a relief compared to the larger incident before. Nevertheless, it’s still frustrating for those affected, and hopefully, the issues will be resolved soon by the Facebook team.
Facebook had another problem today (March 20, 2024). According to Downdetector, a website that shows when other websites are not working, many people had trouble using Facebook.
This isn’t the first time Facebook has had issues. Just a little while ago, there was another problem that stopped people from using the site. Today, when people tried to use Facebook, it didn’t work like it should. People couldn’t see their friends’ posts, and sometimes the website wouldn’t even load.
Downdetector, which watches out for problems on websites, showed that lots of people were having trouble with Facebook. People from all over the world said they couldn’t use the site, and they were not happy about it.
When websites like Facebook have problems, it affects a lot of people. It’s not just about not being able to see posts or chat with friends. It can also impact businesses that use Facebook to reach customers.
Since Facebook owns Messenger and Instagram, the problems with Facebook also meant that people had trouble using these apps. It made the situation even more frustrating for many users, who rely on these apps to stay connected with others.
During this recent problem, one thing is obvious: the internet is always changing, and even big websites like Facebook can have problems. While people wait for Facebook to fix the issue, it shows us how easily things online can go wrong. It’s a good reminder that we should have backup plans for staying connected online, just in case something like this happens again.
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