Zobrazeno 1 - 10
of 1 180
pro vyhledávání: '"CLARK, JACK A."'
Autor:
Maslej, Nestor, Fattorini, Loredana, Perrault, Raymond, Parli, Vanessa, Reuel, Anka, Brynjolfsson, Erik, Etchemendy, John, Ligett, Katrina, Lyons, Terah, Manyika, James, Niebles, Juan Carlos, Shoham, Yoav, Wald, Russell, Clark, Jack
The 2024 Index is our most comprehensive to date and arrives at an important moment when AI's influence on society has never been more pronounced. This year, we have broadened our scope to more extensively cover essential trends such as technical adv
Externí odkaz:
http://arxiv.org/abs/2405.19522
Autor:
Hubinger, Evan, Denison, Carson, Mu, Jesse, Lambert, Mike, Tong, Meg, MacDiarmid, Monte, Lanham, Tamera, Ziegler, Daniel M., Maxwell, Tim, Cheng, Newton, Jermyn, Adam, Askell, Amanda, Radhakrishnan, Ansh, Anil, Cem, Duvenaud, David, Ganguli, Deep, Barez, Fazl, Clark, Jack, Ndousse, Kamal, Sachan, Kshitij, Sellitto, Michael, Sharma, Mrinank, DasSarma, Nova, Grosse, Roger, Kravec, Shauna, Bai, Yuntao, Witten, Zachary, Favaro, Marina, Brauner, Jan, Karnofsky, Holden, Christiano, Paul, Bowman, Samuel R., Graham, Logan, Kaplan, Jared, Mindermann, Sören, Greenblatt, Ryan, Shlegeris, Buck, Schiefer, Nicholas, Perez, Ethan
Humans are capable of strategically deceptive behavior: behaving helpfully in most situations, but then behaving very differently in order to pursue alternative objectives when given the opportunity. If an AI system learned such a deceptive strategy,
Externí odkaz:
http://arxiv.org/abs/2401.05566
Autor:
Maslej, Nestor, Fattorini, Loredana, Brynjolfsson, Erik, Etchemendy, John, Ligett, Katrina, Lyons, Terah, Manyika, James, Ngo, Helen, Niebles, Juan Carlos, Parli, Vanessa, Shoham, Yoav, Wald, Russell, Clark, Jack, Perrault, Raymond
Welcome to the sixth edition of the AI Index Report. This year, the report introduces more original data than any previous edition, including a new chapter on AI public opinion, a more thorough technical performance chapter, original analysis about l
Externí odkaz:
http://arxiv.org/abs/2310.03715
Autor:
Durmus, Esin, Nguyen, Karina, Liao, Thomas I., Schiefer, Nicholas, Askell, Amanda, Bakhtin, Anton, Chen, Carol, Hatfield-Dodds, Zac, Hernandez, Danny, Joseph, Nicholas, Lovitt, Liane, McCandlish, Sam, Sikder, Orowa, Tamkin, Alex, Thamkul, Janel, Kaplan, Jared, Clark, Jack, Ganguli, Deep
Large language models (LLMs) may not equitably represent diverse global perspectives on societal issues. In this paper, we develop a quantitative framework to evaluate whose opinions model-generated responses are more similar to. We first build a dat
Externí odkaz:
http://arxiv.org/abs/2306.16388
Autor:
Shevlane, Toby, Farquhar, Sebastian, Garfinkel, Ben, Phuong, Mary, Whittlestone, Jess, Leung, Jade, Kokotajlo, Daniel, Marchal, Nahema, Anderljung, Markus, Kolt, Noam, Ho, Lewis, Siddarth, Divya, Avin, Shahar, Hawkins, Will, Kim, Been, Gabriel, Iason, Bolina, Vijay, Clark, Jack, Bengio, Yoshua, Christiano, Paul, Dafoe, Allan
Current approaches to building general-purpose AI systems tend to produce systems with both beneficial and harmful capabilities. Further progress in AI development could lead to capabilities that pose extreme risks, such as offensive cyber capabiliti
Externí odkaz:
http://arxiv.org/abs/2305.15324
Autor:
Hadfield, Gillian K., Clark, Jack
Appropriately regulating artificial intelligence is an increasingly urgent policy challenge. Legislatures and regulators lack the specialized knowledge required to best translate public demands into legal requirements. Overreliance on industry self-r
Externí odkaz:
http://arxiv.org/abs/2304.04914
Autor:
Ganguli, Deep, Askell, Amanda, Schiefer, Nicholas, Liao, Thomas I., Lukošiūtė, Kamilė, Chen, Anna, Goldie, Anna, Mirhoseini, Azalia, Olsson, Catherine, Hernandez, Danny, Drain, Dawn, Li, Dustin, Tran-Johnson, Eli, Perez, Ethan, Kernion, Jackson, Kerr, Jamie, Mueller, Jared, Landau, Joshua, Ndousse, Kamal, Nguyen, Karina, Lovitt, Liane, Sellitto, Michael, Elhage, Nelson, Mercado, Noemi, DasSarma, Nova, Rausch, Oliver, Lasenby, Robert, Larson, Robin, Ringer, Sam, Kundu, Sandipan, Kadavath, Saurav, Johnston, Scott, Kravec, Shauna, Showk, Sheer El, Lanham, Tamera, Telleen-Lawton, Timothy, Henighan, Tom, Hume, Tristan, Bai, Yuntao, Hatfield-Dodds, Zac, Mann, Ben, Amodei, Dario, Joseph, Nicholas, McCandlish, Sam, Brown, Tom, Olah, Christopher, Clark, Jack, Bowman, Samuel R., Kaplan, Jared
We test the hypothesis that language models trained with reinforcement learning from human feedback (RLHF) have the capability to "morally self-correct" -- to avoid producing harmful outputs -- if instructed to do so. We find strong evidence in suppo
Externí odkaz:
http://arxiv.org/abs/2302.07459
Autor:
Perez, Ethan, Ringer, Sam, Lukošiūtė, Kamilė, Nguyen, Karina, Chen, Edwin, Heiner, Scott, Pettit, Craig, Olsson, Catherine, Kundu, Sandipan, Kadavath, Saurav, Jones, Andy, Chen, Anna, Mann, Ben, Israel, Brian, Seethor, Bryan, McKinnon, Cameron, Olah, Christopher, Yan, Da, Amodei, Daniela, Amodei, Dario, Drain, Dawn, Li, Dustin, Tran-Johnson, Eli, Khundadze, Guro, Kernion, Jackson, Landis, James, Kerr, Jamie, Mueller, Jared, Hyun, Jeeyoon, Landau, Joshua, Ndousse, Kamal, Goldberg, Landon, Lovitt, Liane, Lucas, Martin, Sellitto, Michael, Zhang, Miranda, Kingsland, Neerav, Elhage, Nelson, Joseph, Nicholas, Mercado, Noemí, DasSarma, Nova, Rausch, Oliver, Larson, Robin, McCandlish, Sam, Johnston, Scott, Kravec, Shauna, Showk, Sheer El, Lanham, Tamera, Telleen-Lawton, Timothy, Brown, Tom, Henighan, Tom, Hume, Tristan, Bai, Yuntao, Hatfield-Dodds, Zac, Clark, Jack, Bowman, Samuel R., Askell, Amanda, Grosse, Roger, Hernandez, Danny, Ganguli, Deep, Hubinger, Evan, Schiefer, Nicholas, Kaplan, Jared
As language models (LMs) scale, they develop many novel behaviors, good and bad, exacerbating the need to evaluate how they behave. Prior work creates evaluations with crowdwork (which is time-consuming and expensive) or existing data sources (which
Externí odkaz:
http://arxiv.org/abs/2212.09251
Autor:
Olsson, Catherine, Elhage, Nelson, Nanda, Neel, Joseph, Nicholas, DasSarma, Nova, Henighan, Tom, Mann, Ben, Askell, Amanda, Bai, Yuntao, Chen, Anna, Conerly, Tom, Drain, Dawn, Ganguli, Deep, Hatfield-Dodds, Zac, Hernandez, Danny, Johnston, Scott, Jones, Andy, Kernion, Jackson, Lovitt, Liane, Ndousse, Kamal, Amodei, Dario, Brown, Tom, Clark, Jack, Kaplan, Jared, McCandlish, Sam, Olah, Chris
"Induction heads" are attention heads that implement a simple algorithm to complete token sequences like [A][B] ... [A] -> [B]. In this work, we present preliminary and indirect evidence for a hypothesis that induction heads might constitute the mech
Externí odkaz:
http://arxiv.org/abs/2209.11895
Autor:
Ganguli, Deep, Lovitt, Liane, Kernion, Jackson, Askell, Amanda, Bai, Yuntao, Kadavath, Saurav, Mann, Ben, Perez, Ethan, Schiefer, Nicholas, Ndousse, Kamal, Jones, Andy, Bowman, Sam, Chen, Anna, Conerly, Tom, DasSarma, Nova, Drain, Dawn, Elhage, Nelson, El-Showk, Sheer, Fort, Stanislav, Hatfield-Dodds, Zac, Henighan, Tom, Hernandez, Danny, Hume, Tristan, Jacobson, Josh, Johnston, Scott, Kravec, Shauna, Olsson, Catherine, Ringer, Sam, Tran-Johnson, Eli, Amodei, Dario, Brown, Tom, Joseph, Nicholas, McCandlish, Sam, Olah, Chris, Kaplan, Jared, Clark, Jack
We describe our early efforts to red team language models in order to simultaneously discover, measure, and attempt to reduce their potentially harmful outputs. We make three main contributions. First, we investigate scaling behaviors for red teaming
Externí odkaz:
http://arxiv.org/abs/2209.07858